CN110444009A - A kind of expressway wagon flow forecasting system based on Internet of Things - Google Patents
A kind of expressway wagon flow forecasting system based on Internet of Things Download PDFInfo
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- CN110444009A CN110444009A CN201810411157.1A CN201810411157A CN110444009A CN 110444009 A CN110444009 A CN 110444009A CN 201810411157 A CN201810411157 A CN 201810411157A CN 110444009 A CN110444009 A CN 110444009A
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- expressway
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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
- G08G1/0129—Traffic data processing for creating historical data or processing based on historical data
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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
- G08G1/0133—Traffic data processing for classifying traffic situation
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- General Physics & Mathematics (AREA)
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Abstract
The expressway wagon flow forecasting system based on Internet of Things that the present invention relates to a kind of.It include: remote server comprising: computing module passes through the time for first calculate each unit expressway；Data acquisition module, for obtaining the online vehicle historical data of each unit expressway in advance；Vehicle wagon flow predictions request module, is installed on vehicle, the wagon flow predictions request for the unit expressway W1 wagon flow that the real time position and needs for obtaining real time position to GPS module, and to remote server transmission including vehicle are predicted；Remote server further include: receiving module, for receiving the wagon flow predictions request of vehicle；Data acquisition module judges the unit expressway W2 where the vehicle also according to the real time position of vehicle, and the real-time traffic flow data A of W2 in real time；Computing module is also used to predict the online wagon flow data of W1；Sending module, for the online wagon flow data of W1 to be sent to vehicle wagon flow predictions request module.Method predictablity rate of the invention is high.
Description
Technical field
The present invention relates to traffic forecast fields, predict system more particularly, to a kind of expressway wagon flow based on Internet of Things
System.
Background technique
It is most important to traffic administration and public safety to the prediction of the magnitude of traffic flow with the high speed development of urban transportation.
But in current city, especially megalopolis, traffic congestion has become a difficult problem of each Urban Traffic, if it is possible in advance
Know that the traffic behavior of road can take preventive measures.Volume forecasting has been increasingly used in the daily life of people
It is living.For example, in the scene of smart city, it can the prediction by the inlet flow rate to specific region, the wagon flow to specific region
The prediction etc. of flow is made rational planning for the running of city items function with information and communication technology (ICT) means, and then in city
People creates more good days, promotes harmony, the Sustainable Growth in city.
But the existing generally existing precision of prediction of volume forecasting scheme it is low, can not be flexible with standardized prediction logic
Suitable for different types of volume forecasting demand.
Summary of the invention
The present invention in order to overcome at least one of the drawbacks of the prior art described above (deficiency), provides a kind of quasi- with high prediction
The expressway wagon flow forecasting system based on Internet of Things of true rate.
In order to solve the above technical problems, technical scheme is as follows:
A kind of expressway wagon flow forecasting system based on Internet of Things, comprising: the wagon flow predictions request module that is installed on vehicle and
Remote server；The wagon flow predictions request module and the GPS module of vehicle, remote server connect；
It is unit expressway, the remote service that section of the expressway between nearest two entrances is defined in remote server
Device includes:
Computing module, for calculating when passing through of the unit expressway according to the minimum speed limit in each unit expressway in advance
Between；
Data acquisition module, for obtaining the online vehicle history number of first entrance each period of each unit expressway in advance
According to；
Vehicle wagon flow predictions request module for obtaining real time position to GPS module, and sends wagon flow prediction to remote server
Request, the wagon flow predictions request includes the real time position of vehicle and the unit expressway W1 wagon flow that needs are predicted；
Remote server further include:
Receiving module, for receiving the wagon flow predictions request of vehicle；
Data acquisition module judges the unit expressway where the vehicle also according to the real time position of vehicle in wagon flow predictions request
W2, and the real-time traffic flow data A of the unit expressway first entrance where the current time T1 vehicle is obtained in real time；
Computing module passes through time prediction also according to real-time traffic flow data A, online vehicle historical data and unit expressway
The online wagon flow data of unit expressway W1；
Sending module, for the online wagon flow data of unit expressway W1 of prediction to be sent to vehicle wagon flow predictions request module.
In above scheme, data acquisition module is specifically used for:
In the daily history week of selection one, which is divided into several periods daily；
Obtain the online wagon flow historical data of daily daily each period in history week；
By the online wagon flow historical data except the time span of this each period obtains averagely existing for daily each period in history week
Line wagon flow historical data.
In above scheme, data acquisition module is also used to:
According to floating certain date before and after the national legal festivals and holidays, period holiday is formed；
Period holiday is divided into several periods daily；
The online wagon flow historical data of obtain period holiday in a certain history year each period daily；
By the online wagon flow historical data except the time span of this each period obtains the average online of in period holiday each period
Wagon flow historical data.
Further include memory module in remote server in above scheme, is used for computing module unit high speed calculated
Road is stored in the table by the time, and, by the average online wagon flow historical data and corresponding unit expressway, period
Storage is in the table.
In above scheme, computing module also particularly useful for:
Calculate the unit expressway passed through required for from W2 to W1, according to the unit expressway passed through by the time calculate from
Time T2 required for W2 to W1；
T3 at the time of predicting that the vehicle reaches W1 according to T2 and T1；
Average online wagon flow historical data, is denoted as L1 and L3 corresponding to period where inquiry T1 and T3
It predicts to obtain the online wagon flow data when vehicle reaches unit expressway W1 using formula A* L3/ L1.
In above scheme, remote server further include: congestion level prejudges module, is used to divide traffic congestion degree
For unimpeded, substantially unimpeded, slight congestion, moderate congestion and heavy congestion；Each traffic congestion degree corresponds to each unit high speed
Online flow threshold is arranged in road；By the vehicle predicted reach unit expressway W1 when online wagon flow data with it is corresponding
Line flow threshold is compared, to predict the traffic congestion degree when vehicle reaches unit expressway W1；
The sending module further includes the online wagon flow data one of unit expressway W1 of the traffic congestion degree and prediction that will predict
It rises and is sent to vehicle wagon flow predictions request module.
Compared with prior art, the beneficial effect of technical solution of the present invention is:
System of the invention carries out expressway to divide the unit expressway for forming a section, respectively to each unit expressway
Normal pass time and online vehicle historical data are calculated and are obtained, then according to the real-time traffic flow of expressway where vehicle
Data predict the unit expressway that vehicle will reach according to historical data, real-time traffic flow data and normal transit time
Online wagon flow data when vehicle is reached according to normal time, historical data, real-time traffic flow data and normal pass time phase
In conjunction with being predicted, predictablity rate is high.
Detailed description of the invention
Fig. 1 is a kind of frame diagram of the expressway wagon flow forecasting system based on Internet of Things of the present invention.
Specific embodiment
The attached figures are only used for illustrative purposes and cannot be understood as limitating the patent；
In order to better illustrate this embodiment, the certain components of attached drawing have omission, zoom in or out, and do not represent the ruler of actual product
It is very little；
To those skilled in the art, the omitting of some known structures and their instructions in the attached drawings are understandable.
In the description of the present invention, it is to be understood that, in addition, term " first ", " second " are used for description purposes only, and
It cannot be understood as indicating or implying relative importance or imply the quantity of indicated technical characteristic." first " that limits as a result,
One or more of the features can be expressed or be implicitly included to the feature of " second ".In the description of the present invention, unless separately
It is described, the meaning of " plurality " is two or more.
In the description of the present invention, it should be noted that unless otherwise clearly defined and limited, term " installation " " connects
Connect " it shall be understood in a broad sense, for example, it may be being fixedly connected, it may be a detachable connection, or be integrally connected；It can be machine
Tool connection, is also possible to be electrically connected；It can be directly connected, be also possible to be indirectly connected with by intermediary, it may be said that two
Connection inside element.For the ordinary skill in the art, above-mentioned term can be understood in the present invention with concrete condition
Concrete meaning.
The following further describes the technical solution of the present invention with reference to the accompanying drawings and examples.
Embodiment 1
As shown in Figure 1, for a kind of frame diagram of the expressway wagon flow forecasting system based on Internet of Things of the present invention.Referring to Fig. 1, this hair
A kind of bright expressway wagon flow forecasting system based on Internet of Things specifically includes: the wagon flow predictions request module being installed on vehicle
101 and remote server 102；The wagon flow predictions request module 101 is connect with the GPS module 103 of vehicle, remote server 102；
It is unit expressway, this definition that section of the expressway between nearest two entrances is defined in remote server 102
It is that expressway is divided into a section, predictablity rate is high is predicted to the vehicle flowrate of every section of expressway to realize.
Remote server 102 includes computing module 1021, data acquisition module 1022, receiving module 1023, sending module
1024, congestion level prejudges module 1025, memory module 1026；
Computing module 1021, for calculating passing through for the unit expressway according to the minimum speed limit in each unit expressway in advance
Time；Unit expressway calculated is stored in memory module 1026 by the time, should by the time storage when and unit
Expressway is one-to-one to be stored, and can inquire corresponding pass through according to unit expressway in memory module 1026 so as to subsequent
Time.
Data acquisition module 1022, for obtaining the online vehicle of first entrance each period of each unit expressway in advance
Historical data；Its concrete implementation mode are as follows:
In the daily history week of selection one, which is divided into several periods daily；The selection in the daily history week
It can be to reselect in every month or each season primary and re-execute below step to update online vehicle historical data.Often
The division of its period can be divided as unit of a hour, can also be selected according to traffic peak, flat peak and night-time hours
Select suitable division mode.
Obtain the online wagon flow historical data of daily daily each period in history week；
By the online wagon flow historical data except the time span of this each period obtains averagely existing for daily each period in history week
Line wagon flow historical data.Time span refers to the time span for being included in a period, such as unit of a hour
The obtained period is divided, then the span of a hour is 60 minutes, 60 minutes can be calculated as time span and averagely be existed
Line wagon flow historical data.
In addition, it is contemplated that very big, of the invention data acquisition module is distinguished with the wagon flow data of festivals or holidays on ordinary days in expressway
1022 also by especially obtaining the online wagon flow historical data of national legal festivals and holidays as the basic data of prediction, specifically
:
According to floating certain date before and after the national legal festivals and holidays, period holiday is formed；Such as according to national regulation member in 2018
The time of having a holiday or vacation of denier is 2017.12.30-2018.1.1, then can choose 2017.12.29-2018.1.2 and form week holiday on New Year's Day
Phase.
Period holiday is divided into several periods daily；Likewise, the division of period can be with a hour daily
It is divided for unit, suitable division mode can also be selected according to traffic peak, flat peak and night-time hours.
The online wagon flow historical data of obtain period holiday in a certain history year each period daily；It implemented
Cheng Zhong, the historical data for obtaining previous year is the most accurate, and therefore, the historical data in period holiday can be with 1 year when specific operation
It updates primary.
By the online wagon flow historical data except the time span of this each period obtains being averaged in period holiday each period
Online wagon flow historical data.
By average online wagon flow historical data obtained in data acquisition module 1022 and corresponding unit expressway, period
It is stored in memory module 1026.
Vehicle wagon flow predictions request module 101, for obtaining real time position to GPS module 103, and to remote server
102 send wagon flow predictions request, and the wagon flow predictions request includes the real time position of vehicle and the unit high speed that needs are predicted
Road W1 wagon flow；
Receiving module 1023, for receiving the wagon flow predictions request of vehicle；
Unit where data acquisition module 1022 judges the vehicle also according to the real time position of vehicle in wagon flow predictions request is high
Fast road W2, and the real-time traffic flow data A of the unit expressway first entrance where the current time T1 vehicle is obtained in real time；
Computing module 1021 passes through the time also according to real-time traffic flow data A, online vehicle historical data and unit expressway
Predict the online wagon flow data of unit expressway W1；It is specific:
The unit expressway passed through required for calculating from W2 to W1 obtains passed through unit height by inquiring memory module 1026
Fast road by the time, to calculate time T2 required for from W2 to W1；
T3 at the time of predicting that the vehicle reaches W1 according to T2 and T1；
Average online wagon flow historical data corresponding to the period where T1 and T3 is inquired by memory module 1026, be denoted as L1 and
L3
It predicts to obtain the online wagon flow data when vehicle reaches unit expressway W1 using formula A* L3/ L1.
In the prediction mode, predicts that the vehicle reaches the time of W1 at the time of by obtaining data in real time, pass through and be
Number obtains the online wagon flow of the unit expressway reached when unit expressway and the prediction that the vehicle is currently located than L3/ L1
The coefficient ratio of historical data, to predict to obtain the online wagon flow data of unit expressway W1 based on accessed A.This mode
Predictablity rate is high, and the real-time prediction of online wagon flow may be implemented.
Congestion level prejudge module 1025, for by traffic congestion degree be divided into unimpeded, substantially unimpeded, slight congestion,
Moderate congestion and heavy congestion；Each traffic congestion degree corresponds to each unit expressway and online flow threshold is arranged；It will prediction
To the vehicle reach unit expressway W1 when online wagon flow data be compared with corresponding online flow threshold, thus in advance
Survey the traffic congestion degree when vehicle reaches unit expressway W1；Model is prejudged by congestion level come online to what is predicted
Wagon flow data carry out congestion level judgement, bring intuitive congestion to judge for user, promote user experience.
Sending module 1024, the online wagon flow data of unit expressway W1, the traffic congestion degree of prediction for that will predict
It is sent to vehicle wagon flow predictions request module 101.
The same or similar label correspond to the same or similar components；
Described in attached drawing positional relationship for only for illustration, should not be understood as the limitation to this patent；
Obviously, the above embodiment of the present invention be only to clearly illustrate example of the present invention, and not be to this hair
The restriction of bright embodiment.For those of ordinary skill in the art, it can also do on the basis of the above description
Other various forms of variations or variation out.There is no necessity and possibility to exhaust all the enbodiments.It is all in the present invention
Spirit and principle within made any modifications, equivalent replacements, and improvements etc., should be included in the guarantor of the claims in the present invention
Within the scope of shield.
Claims (6)
1. a kind of expressway wagon flow forecasting system based on Internet of Things characterized by comprising the wagon flow being installed on vehicle is pre-
Survey request module and remote server；The wagon flow predictions request module and the GPS module of vehicle, remote server connect；
It is unit expressway, the remote service that section of the expressway between nearest two entrances is defined in remote server
Device includes:
Computing module, for calculating when passing through of the unit expressway according to the minimum speed limit in each unit expressway in advance
Between；
Data acquisition module, for obtaining the online vehicle history number of first entrance each period of each unit expressway in advance
According to；
Vehicle wagon flow predictions request module for obtaining real time position to GPS module, and sends wagon flow prediction to remote server
Request, the wagon flow predictions request includes the real time position of vehicle and the unit expressway W1 wagon flow that needs are predicted；
Remote server further include:
Receiving module, for receiving the wagon flow predictions request of vehicle；
Data acquisition module judges the unit expressway where the vehicle also according to the real time position of vehicle in wagon flow predictions request
W2, and the real-time traffic flow data A of the unit expressway first entrance where the current time T1 vehicle is obtained in real time；
Computing module passes through time prediction also according to real-time traffic flow data A, online vehicle historical data and unit expressway
The online wagon flow data of unit expressway W1；
Sending module, for the online wagon flow data of unit expressway W1 of prediction to be sent to vehicle wagon flow predictions request module.
2. the expressway wagon flow forecasting system according to claim 1 based on Internet of Things, which is characterized in that data acquisition mould
Block is specifically used for:
In the daily history week of selection one, which is divided into several periods daily；
Obtain the online wagon flow historical data of daily daily each period in history week；
By the online wagon flow historical data except the time span of this each period obtains averagely existing for daily each period in history week
Line wagon flow historical data.
3. the expressway wagon flow forecasting system according to claim 2 based on Internet of Things, which is characterized in that data acquisition mould
Block is also used to:
According to floating certain date before and after the national legal festivals and holidays, period holiday is formed；
Period holiday is divided into several periods daily；
The online wagon flow historical data of obtain period holiday in a certain history year each period daily；
By the online wagon flow historical data except the time span of this each period obtains the average online of in period holiday each period
Wagon flow historical data.
4. the expressway wagon flow forecasting system according to claim 3 based on Internet of Things, which is characterized in that remote server
In further include memory module, for by computing module unit expressway calculated by time storage in the table, and,
The average online wagon flow historical data is stored in the table with corresponding unit expressway, period.
5. the expressway wagon flow prediction technique according to claim 4 based on Internet of Things, which is characterized in that computing module is also
It is specifically used for:
Calculate the unit expressway passed through required for from W2 to W1, according to the unit expressway passed through by the time calculate from
Time T2 required for W2 to W1；
T3 at the time of predicting that the vehicle reaches W1 according to T2 and T1；
Average online wagon flow historical data, is denoted as L1 and L3 corresponding to period where inquiry T1 and T3
It predicts to obtain the online wagon flow data when vehicle reaches unit expressway W2 using formula A* L3/ L1.
6. the expressway wagon flow prediction technique according to claim 5 based on Internet of Things, which is characterized in that remote server
Further include: congestion level prejudges module, is used to for traffic congestion degree to be divided into unimpeded, substantially unimpeded, slight congestion, moderate
Congestion and heavy congestion；Each traffic congestion degree corresponds to each unit expressway and online flow threshold is arranged；By what is predicted
Online wagon flow data when the vehicle reaches unit expressway W1 are compared with corresponding online flow threshold, so that prediction should
Vehicle reaches the traffic congestion degree when W1 of unit expressway；
The sending module further includes the online wagon flow data one of unit expressway W1 of the traffic congestion degree and prediction that will predict
It rises and is sent to vehicle wagon flow predictions request module.
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Cited By (1)
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| CN115331439A (en) * | 2022-08-09 | 2022-11-11 | 山东旗帜信息有限公司 | Vehicle history image-based highway interchange traffic flow prediction method and system |
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