CN107833459A - A kind of city bus operation conditions evaluation method based on gps data - Google Patents
A kind of city bus operation conditions evaluation method based on gps data Download PDFInfo
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/20—Monitoring the location of vehicles belonging to a group, e.g. fleet of vehicles, countable or determined number of vehicles
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
- G08G1/0108—Measuring and analyzing of parameters relative to traffic conditions based on the source of data
- G08G1/0112—Measuring and analyzing of parameters relative to traffic conditions based on the source of data from the vehicle, e.g. floating car data [FCD]
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
- G08G1/0125—Traffic data processing
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Abstract
The invention discloses a kind of city bus operation conditions evaluation method based on gps data, it comprises the following steps：Step 1, according to the gps data and GIS data of the city bus in certain section, the average speed of all public transit vehicles in every 5 minutes sections in a period is calculated, the section includes through street, trunk roads and branch road；Step 2, the average speed in step 1 is modified using the method for exponential smoothing；Step 3, calculate the average speed of system-wide section；Step 4, the average speed of step 3 is converted into the index that passes unimpeded.A kind of city bus operation conditions evaluation method based on gps data of the present invention, using the operation characteristic index of gps data extraction city bus to public transport operation status evaluation, using public transit vehicle individual as object, running status of the vehicle in fixed circuit can be reflected, by the multidate information for analyzing public transit vehicle, running status of the bus in the time and space can really be presented, more accurately evaluate the operational efficiency of bus.
Description
Technical field
The present invention relates to Urban Transportation planning field, more particularly to a kind of city bus operation based on gps data
Status evaluation method.
Background technology
Urban public transport is the sustainer of transportation service industry, is had to development such as the politics, economy, environment in city
Have a major impact.Compared with car, public transport has that fortune volume of passenger traffic is big, energy-conserving and environment-protective advantage, effectively alleviates Chinese
Equal landed property area is small, and the fundamental realities of the country that petroleum-based energy is rare.The sharp increase of private car recoverable amount has triggered energy mistake
Spend consumption, the urban issues such as traffic jam, and conveniently public transport provides the traffic of equality for most people and gone out
Row power, embodies the justice and efficiency of society, and it develops the performance for being directly connected to city allomeric function.To the end of the year 2013, I
The transport total amount of state's urban transit bus and electric car reaches 881.42 hundred million person-times, national bus and electric car operating line
41738,74.9 ten thousand kilometers of operating line overall length.
The operation conditions of accurate evaluation urban public tranlport system is to build the first step of efficient public transport, in the past side
Method lays particular emphasis on the overall traffic operation situation of road.Many city traffic management departments domestic at present and trip information service are public
Department has carried out the research and application of traffic index model, such as Beijing, Guangzhou, Nanjing, Shenzhen, Shanghai, Gao De, four new figures, drops
Drop etc., its exponential model computational methods can substantially be classified as to be commented based on heavy congestion mileage ratio, travel time ratio and mixing
Several classes such as valency method.Beijing takes the lead in carrying out road traffic assessment item at home, establishes traffic congestion assessment indicator system
And evaluation method, using heavy congestion mileage than evaluation method, section running status is divided into unimpeded, substantially unimpeded, light
Spend 5 kinds of congestion, moderate congestion and heavy congestion states.Heavy congestion mileage ratio is defined as in certain statistics time interval,
Each grade road is in the section mileage ratio of heavy congestion grade in road network.The historical traffic information number that high moral is accumulated based on it
According to using evaluation index of the congestion delay index as urban congestion degree；NavInfo is in the actual speed of road and current
On conditioned basic, the subjective feeling to traffic congestion is added, using quantification Index Assessment road traffic operation conditions.
At present, above-mentioned Traffic Evaluation exponential model is all based on the overall traffic operation situation of road, lacks for city
The method of the operation conditions evaluation of public transport.And the operation conditions of public transit system is evaluated exactly for improving urban public transport
It is most important.
The content of the invention
The purpose of the present invention is to solve the shortcomings of the prior art and provide a kind of city bus fortune based on gps data
Row status evaluation method, using the operation characteristic index of gps data extraction city bus to public transport operation status evaluation, with public affairs
Friendship vehicle individual is object, can reflect running status of the vehicle in fixed circuit, be believed by the dynamic for analyzing public transit vehicle
Breath, can really be presented running status of the bus in the time and space, more accurately evaluate the operation effect of bus
Rate.
To reach above-mentioned purpose, the present invention is achieved through the following technical solutions.
A kind of city bus operation conditions evaluation method based on gps data, it comprises the following steps：
Step 1, according to the gps data and GIS data of the city bus in certain section, calculate in a period every 5 minutes
The average speed of all public transit vehicles in the section, the section include through street, trunk roads and branch road；
Step 2, the average speed in step 1 is modified using the method for exponential smoothing；
Step 3, calculate the average speed of system-wide section；
Step 4, the average speed of step 3 is converted into the index that passes unimpeded.
Further, the average speed in the step 1Computational methods be：
Wherein, j represents jth bus, tjsRepresent the first record time of jth bus, tjdRepresent jth public affairs
Hand over the termination record time of car；SjsRepresent the first record operation mileage of jth bus, SjdRepresent jth bus
Terminate record operation mileage, VjRepresent jth bus some 5 minutes average speed in the section certain period of time.
Further, the average speed amendment step for stating step 2 is：
The first step, the average speed degree in the section of certain period areIt can be expressed as：
Wherein, VjRepresent the average speed of some bus in some 5 minutes of the section a certain period, j tables
Show jth bus, tjsRepresent the first record time of jth bus, tjdWhen representing the termination record of jth bus
Between；SjsThe first record operation mileage of jth bus, is SjdRepresent the termination record operation mileage of jth bus.
A kind of city bus operation conditions evaluation method based on gps data of the present invention, city is extracted using gps data
The operation characteristic index of city's public transport using public transit vehicle individual as object, can reflect vehicle solid public transport operation status evaluation
The running status on alignment road, by analyzing the multidate information of public transit vehicle, bus can really be presented in the time and space
In running status, more accurately evaluate bus operational efficiency.
Embodiment
With reference to embodiment, the present invention will be further described, but is not limited to the content on specification.
By taking Zhengzhou City's public transit system as an example, the present invention includes following steps：
Step 1: section speed calculates
According to public transit system feature and data result, the public transport index assessment that passes unimpeded selects speed index.With reference to gps data
Structure and the Zhengzhou City's GIS data file grasped, index is counted based on choosing section bus average speed
Calculate.In order to improve evaluation precision, it is the counting period to choose 5 minutes, i.e., calculates an average speed within every five minutes.Draw in section
Divide according to being according to position residing for road and important node, distinguish current direction and divide evaluation path.In road network system,
The running velocity of different brackets road is different, equally applicable for public transportation system.Public transit vehicle is in different brackets road
Road travelling speed is different, also different to the contribution rate of whole road network operation conditions.When therefore evaluating public transport network, have
It is necessary that grade classification is carried out to road network, different grades of classification of road is not analyzed, to carry out scientific and reasonable evaluation.
In GB50220-95, city entirety road network is divided into four through street, trunk roads, secondary distributor road, branch road grades.
A) through street refers to be provided with median strip in urban road, and unidirectional set is no less than two tracks, all uses
Crossings on different level comes in and goes out with control, realizes the road that traffic is continuously passed through.
B) trunk roads refer to connect each major divisions in city, the road based on communication function in urban road network.
C) secondary distributor road refers to being combined with trunk roads in urban road network, based on the function of collecting and distributing traffic, has service concurrently
The road of function.
D) branch road refers to the internal passageway such as secondary distributor road and residential area, industrial area, means of transportation be connected in urban road network
Connect, solve the road of some areas service function.
Because secondary distributor road is similar to branch road attribute, speed of service difference is little, and the bus routes of branch road are few,
Secondary distributor road and branch road are classified as same grade by the applicability overall from model, this research.So, transported to public transport
Row situation is carried out in evaluation procedure, and road network is divided into Three Estate, i.e. through street, trunk roads and branch road.Through street should be with discrepancy
Mouth is segmented for end points, and road section length answers re-segmenting trunk roads, secondary distributor road, branch road should be with stop line more than or equal to 3 kilometers
It is segmented for end points, i.e., upstream stop line to downstream stop line is a section, and road section length is more than or equal to 1.5 kilometers should
Re-segmenting.
This experimental system evaluates the period based on using 5 minutes, and evaluation is used as by the use of operation average speed between bus stop
Base values, mileage is mainly runed according to gps data, positioning time calculated.
The average speed in website AB sections in i-th five minutes is calculated as block section between stations public transport operation evaluation index.
First according to all records in gps data and the period of GIS map data matching inquiry i-th in website AB.Wherein by website
Terminal of the B point leaving from station as section.N bus is included in all records altogether, during the first record of jth bus
Between be tjs, it is t to terminate the record timejd；First record operation mileage is sjs, it is s to terminate record operation mileagejd, then bus
Travel speeds AB section in of the j in the i-th period be
Then the average vehicle speed in period i in the AB of section isIt can be expressed as：
Public transport travelling speed is needed within the scope of one rational, and the travelling speed by being calculated, and can be produced
Some exceptional values, speed is very big or very small, is not inconsistent with actual operating state.This just needs to need for some exceptional values
Handled, setting bus section travelling speed threshold value, handled for the data more than threshold value.The rule of judgement
It is as follows：
(1) through street section speed is more than 65km/h and is less than travelling speed value between 75km/h website, with previous station
The travelling speed data of point and the latter website carry out mean value calculation, the travelling speed value using this value as this three websites.
(2) trunk roads section speed is more than 55km/h and is less than travelling speed value between 65km/h website, with previous station
The travelling speed data of point and the latter website carry out mean value calculation, the travelling speed value using this value as this three websites.
(3) secondary distributor road section speed is more than 45km/h and is less than travelling speed value between 55km/h website, with previous station
The travelling speed data of point and the latter website carry out mean value calculation, the travelling speed value using this value as this three websites.
(4) through street section travelling speed is more than 75km/h, trunk roads section travelling speed is more than 65km/h, secondary distributor road
Section travelling speed is more than 55km/h data, all rejects.
Step 2: section speed amendment
When establishing public transport operation status evaluation system, for given road network, it is necessary to how many bus samples
Accurate, comprehensive Traffic Information could be provided, be the major issue for needing to solve.Bus sample size was both related to
The construction of system and operating cost, are also related to accuracy of data acquisition.It is simultaneously noticeable that to be due to that bus has fixed
Timetable and departure interval, so a certain section may not have bus to pass through in certain time period, except no theory
Period be also algorithm should consider a bit.
Made referrals on trifle in period i section, the average speed estimate of n car isObviously, n is bigger, and the error between link average speed estimation value and actual value is smaller,
But the quality of data require it is higher, it is desirable to sampling interval with regard to smaller.Show that vehicle average speed is approximate according to research and obey normal state
It is distributed N (v, σ2), the sampling theorem in mathematical statistics, the section mean speed of n table flotation motor-carsObey
If n table flotation motor-car section mean speedsError with actual section mean speed is less than limits of error ε's
Probability is not less than 1- α：
It can obtain
It is and Road average-speed standard deviation by the bus sample size required for wall scroll section it can be seen from the formula
σ, confidence level 1- α and the limits of error ε correlations variable.Being calculated according to different road types can be calculated not
Minimum public transit vehicle number in same type.
The velocity amplitude calculated using gps data can be modified according to the minimum vehicle number of determination.When public on section
When handing over the car quantity to be more than the minimum samples needed, the average speed that is calculated using gps data and the error of actual value compared with
It is small.When the bus within a calculating cycle (5min) in section is not reaching to smallest sample number demand, now result of calculation
It there may be certain error.For this problem, this research is calculated using the EXSMOOTH of adaptive weighting
Section mean speed.
Exponential smoothing is a kind of method for the processing time series data commonly used in research.The simple full period method of average is pair
The past data one of time series does not leak ground and all utilized on an equal basis；Rolling average rule does not consider data more at a specified future date,
And give recent data bigger weight in the method for weighted moving average；And the compatible full period of exponential smoothing rule is average and moves
The dynamic average chief, does not give up past data, but is given only the influence degree gradually weakened, i.e., remote with data,
Imparting gradually converges to zero flexible strategy.Exponential smoothing is a kind of time series to grow up on the basis of the method for moving average
Predicted method is analyzed, it is by gauge index smooth value, coordinates regular hour sequential forecasting models to carry out the future of phenomenon
Prediction.Its principle is that the exponential smoothing value of any phase is all that current period actual observation value and the weighting of previous phase index smooth value are put down
.The formula of exponential smoothing is in this research：
Equal to the average speed of objective time interval,For the speed of a upper period, f (m) weighs for exponential smoothing
Weight：
Wherein njFor the vehicle number in period section.nminIt is the parameter value of input, represents to want on each road
The minimum vehicle number asked.
Utilization index smoothly can preferably handle that public transit vehicle number in section is less or situation without bus,
The operation conditions of bus is more accurately described.
Step 3: section speed weights
The speed of bus has positive and negative build-up effect for the index that passes unimpeded.Positive and negative build-up effect is each speed for smooth
Row index is all influential, and low speed produces negative effect, and this effect is strengthened with the increase of low speed number, with low speed
The reduction of number and weaken；Positive-effect is produced at a high speed, and this effect is strengthened with the increase of high speed number, with individual at a high speed
Several reduction and weaken.Therefore can be using the mode of weighted calculation come the positive and negative build-up effect of processing speed.Each speed
Influence to the index that passes unimpeded is different, according to speed and the linear relationship and actual conditions of the index that passes unimpeded, to each speed
Add a weighted value.
Using the average speed and exponential smoothing of a upper trifle can obtain one the period each section average speed.
When calculating the speed value of whole network, it is weighted according to road type to different speed.
Wherein weight w is exactly the different weighted value of the different road types inputted.Following table is the speed weight on trunk roads
Value.The weighted value of different road types can determine according to different types of velocity interval.
The trunk roads speed weight of table 1
Step 4: index conversion of passing unimpeded
Need velocity amplitude transfer turning into the index that passes unimpeded after speed is calculated, therefore velocity amplitude is relatively abstract, no
It is readily understood, it is difficult to be contrasted.This research passes unimpeded index design as the not synchronized of the corresponding different road types of 5 levels
Degree, specific index conversion are as shown in the table：
The speed of table 2 passes unimpeded index conversion table
A kind of city bus operation conditions evaluation method based on gps data of the present invention, city is extracted using gps data
The operation characteristic index of city's public transport using public transit vehicle individual as object, can reflect vehicle solid public transport operation status evaluation
The running status on alignment road, by analyzing the multidate information of public transit vehicle, bus can really be presented in the time and space
In running status, more accurately evaluate bus operational efficiency.
Obviously, above-mentioned embodiment of the invention is only intended to clearly illustrate example of the present invention, and is not
Restriction to embodiments of the present invention.For those of ordinary skill in the field, on the basis of the above description also
It can make other changes in different forms.Here all embodiments can not be exhaustive.It is every to belong to this
Row of the obvious changes or variations that the technical scheme of invention is extended out still in protection scope of the present invention.
Claims (3)
- A kind of 1. city bus operation conditions evaluation method based on gps data, it is characterised in that：It comprises the following steps：Step 1, according to the gps data and GIS data of the city bus in certain section, calculate every 5 minutes sections in a period The average speed of all public transit vehicles, the section include through street, trunk roads and branch road；Step 2, the average speed in step 1 is modified using the method for exponential smoothing；Step 3, calculate the average speed of system-wide section；Step 4, the average speed of step 3 is converted into the index that passes unimpeded.
- 2. a kind of city bus operation conditions evaluation method based on gps data according to claim 1, its feature exist In：Average speed in the step 1Computational methods be：<mrow> <mover> <mi>V</mi> <mo>&OverBar;</mo> </mover> <mo>=</mo> <mfrac> <mn>1</mn> <mi>n</mi> </mfrac> <munderover> <mo>&Sigma;</mo> <mrow> <mi>j</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>n</mi> </munderover> <msub> <mi>V</mi> <mi>j</mi> </msub> </mrow><mrow> <msub> <mi>V</mi> <mi>j</mi> </msub> <mo>=</mo> <mfrac> <mrow> <msub> <mi>S</mi> <mrow> <mi>j</mi> <mi>d</mi> </mrow> </msub> <mo>-</mo> <msub> <mi>S</mi> <mrow> <mi>j</mi> <mi>s</mi> </mrow> </msub> </mrow> <mrow> <msub> <mi>t</mi> <mrow> <mi>j</mi> <mi>d</mi> </mrow> </msub> <mo>-</mo> <msub> <mi>t</mi> <mrow> <mi>j</mi> <mi>s</mi> </mrow> </msub> </mrow> </mfrac> </mrow>Wherein, j represents jth bus, tjsRepresent the first record time of jth bus, tjdRepresent jth bus Terminate the record time；SjsRepresent the first record operation mileage of jth bus, SjdRepresent the termination record of jth bus Run mileage, VjRepresent jth bus some 5 minutes average speed in the section certain period of time.
- 3. a kind of city bus operation conditions evaluation method based on gps data according to claim 1, its feature exist In：The average speed amendment step of the step 2 is：The first step, the average speed degree in the section of certain period areIt can be expressed as：<mrow> <mover> <mi>V</mi> <mo>&OverBar;</mo> </mover> <mo>=</mo> <mfrac> <mn>1</mn> <mi>n</mi> </mfrac> <munderover> <mo>&Sigma;</mo> <mrow> <mi>j</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>n</mi> </munderover> <msub> <mi>V</mi> <mi>j</mi> </msub> <mo>=</mo> <mfrac> <mn>1</mn> <mi>n</mi> </mfrac> <munderover> <mo>&Sigma;</mo> <mrow> <mi>j</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>n</mi> </munderover> <mfrac> <mrow> <msub> <mi>S</mi> <mrow> <mi>j</mi> <mi>d</mi> </mrow> </msub> <mo>-</mo> <msub> <mi>S</mi> <mrow> <mi>j</mi> <mi>s</mi> </mrow> </msub> </mrow> <mrow> <msub> <mi>t</mi> <mrow> <mi>j</mi> <mi>d</mi> </mrow> </msub> <mo>-</mo> <msub> <mi>t</mi> <mrow> <mi>j</mi> <mi>s</mi> </mrow> </msub> </mrow> </mfrac> </mrow>Wherein, VjThe average speed of some bus in some 5 minutes of the section a certain period is represented, j represents jth Bus, tjsRepresent the first record time of jth bus, tjdRepresent the termination record time of jth bus；Sjs The first record operation mileage of jth bus, is SjdRepresent the termination record operation mileage of jth bus.
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Application publication date: 20180323 |