CN109360416A - Road traffic prediction technique and server - Google Patents

Road traffic prediction technique and server Download PDF

Info

Publication number
CN109360416A
CN109360416A CN201811181962.6A CN201811181962A CN109360416A CN 109360416 A CN109360416 A CN 109360416A CN 201811181962 A CN201811181962 A CN 201811181962A CN 109360416 A CN109360416 A CN 109360416A
Authority
CN
China
Prior art keywords
section
measured
data
vehicle
congestion
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.)
Pending
Application number
CN201811181962.6A
Other languages
Chinese (zh)
Inventor
吴壮伟
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Ping An Technology Shenzhen Co Ltd
Original Assignee
Ping An Technology Shenzhen Co Ltd
Priority date (The priority date 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 date listed.)
Filing date
Publication date
Application filed by Ping An Technology Shenzhen Co Ltd filed Critical Ping An Technology Shenzhen Co Ltd
Priority to CN201811181962.6A priority Critical patent/CN109360416A/en
Publication of CN109360416A publication Critical patent/CN109360416A/en
Pending legal-status Critical Current

Links

Classifications

    • GPHYSICS
    • G08SIGNALLING
    • G08GTRAFFIC CONTROL SYSTEMS
    • G08G1/00Traffic control systems for road vehicles
    • G08G1/01Detecting movement of traffic to be counted or controlled
    • G08G1/0104Measuring and analyzing of parameters relative to traffic conditions
    • G08G1/0108Measuring and analyzing of parameters relative to traffic conditions based on the source of data
    • G08G1/0112Measuring and analyzing of parameters relative to traffic conditions based on the source of data from the vehicle, e.g. floating car data [FCD]
    • GPHYSICS
    • G08SIGNALLING
    • G08GTRAFFIC CONTROL SYSTEMS
    • G08G1/00Traffic control systems for road vehicles
    • G08G1/01Detecting movement of traffic to be counted or controlled
    • G08G1/0104Measuring and analyzing of parameters relative to traffic conditions
    • G08G1/0108Measuring and analyzing of parameters relative to traffic conditions based on the source of data
    • G08G1/0116Measuring and analyzing of parameters relative to traffic conditions based on the source of data from roadside infrastructure, e.g. beacons
    • GPHYSICS
    • G08SIGNALLING
    • G08GTRAFFIC CONTROL SYSTEMS
    • G08G1/00Traffic control systems for road vehicles
    • G08G1/01Detecting movement of traffic to be counted or controlled
    • G08G1/0104Measuring and analyzing of parameters relative to traffic conditions
    • G08G1/0125Traffic data processing
    • G08G1/0133Traffic data processing for classifying traffic situation
    • GPHYSICS
    • G08SIGNALLING
    • G08GTRAFFIC CONTROL SYSTEMS
    • G08G1/00Traffic control systems for road vehicles
    • G08G1/065Traffic control systems for road vehicles by counting the vehicles in a section of the road or in a parking area, i.e. comparing incoming count with outgoing count

Landscapes

  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Chemical & Material Sciences (AREA)
  • Analytical Chemistry (AREA)
  • Traffic Control Systems (AREA)

Abstract

The present invention is suitable for computer application technology, provide a kind of road traffic prediction technique, server and computer readable storage medium, it include: the vehicle flowrate data by obtaining the section to be measured that road monitoring apparatus is sent, and the traveling data that the terminal in the vehicle in section to be measured is sent;According to vehicle flowrate data, traveling data and the default road information in section to be measured, the congestion coefficient in section to be measured is calculated;Determine whether section to be measured is congestion section according to congestion coefficient and preset congestion threshold.The traveling data of the vehicle termination in vehicle flowrate data and section to be measured by obtaining the section to be measured of road monitoring apparatus transmission simultaneously, and it is combined according to vehicle flowrate data and traveling data and congestion coefficient is calculated, to judge whether current road segment occurs congestion by congestion coefficient, the accuracy and integrality for improving road congestion judgement, the road traffic control for after provide good data basis.

Description

Road traffic prediction technique and server
Technical field
The invention belongs to computer application technology more particularly to a kind of road traffic prediction techniques, server and meter Calculation machine readable storage medium storing program for executing.
Background technique
There is the urban road traffic network of oneself in each city, and people are by selecting different routes that can quickly reach The destination of oneself.However, many times due to traffic congestion, if still according to previous traffic path, user will It is difficult to reach the destination of oneself in regulation duration.It is well known that urban road congestion is a kind of dynamic congestion, Er Feijing The congestion of state.This also means that the degree of road congestion changes with the variation of duration.
In the prior art by being monitored to Traffic Information, current traffic congestion situation is determined.But it is this Mode in the case where vehicle flowrate changes at random, can not comprehensively, calculate to a nicety to obtain road congestion situation.
Summary of the invention
In view of this, the embodiment of the invention provides a kind of road traffic prediction technique, server and computer-readable depositing Storage media, to solve in the prior art in the case where vehicle flowrate change at random, can not it is comprehensive, calculate to a nicety to obtain road The problem of congestion.
The first aspect of the embodiment of the present invention provides a kind of road traffic prediction technique, comprising:
Obtain the vehicle flowrate data in the section to be measured that road monitoring apparatus is sent, and the vehicle in the section to be measured In terminal send traveling data;
According to the default road information of the vehicle flowrate data, the traveling data and the section to be measured, institute is calculated State the congestion coefficient in section to be measured;
Determine whether the section to be measured is congestion section according to the congestion coefficient and preset congestion threshold.
The second aspect of the embodiment of the present invention provides a kind of server, including memory, processor and is stored in institute The computer program that can be run in memory and on the processor is stated, the processor executes real when the computer program Existing following steps:
Obtain the vehicle flowrate data in the section to be measured that road monitoring apparatus is sent, and the vehicle in the section to be measured In terminal send traveling data;
According to the default road information of the vehicle flowrate data, the traveling data and the section to be measured, institute is calculated State the congestion coefficient in section to be measured;
Determine whether the section to be measured is congestion section according to the congestion coefficient and preset congestion threshold.The present invention The third aspect of embodiment provides a kind of computer readable storage medium, and the computer storage medium is stored with computer journey Sequence, the computer program include program instruction, and described program instruction when being executed by a processor executes the processor The method for stating first aspect.
Existing beneficial effect is the embodiment of the present invention compared with prior art:
The embodiment of the present invention by obtain road monitoring apparatus send section to be measured vehicle flowrate data, and in The traveling data that the terminal surveyed in the vehicle in section is sent;According to the default of vehicle flowrate data, traveling data and section to be measured Road information calculates the congestion coefficient in section to be measured;Whether section to be measured is determined according to congestion coefficient and preset congestion threshold For congestion section.On vehicle flowrate data and section to be measured by obtaining the section to be measured of road monitoring apparatus transmission simultaneously The traveling data of vehicle termination, and combined according to vehicle flowrate data and traveling data and congestion coefficient is calculated, to pass through congestion Coefficient judges whether current road segment occurs congestion, improves the accuracy and integrality of road congestion judgement, the road after being Traffic control provides good data basis.
Detailed description of the invention
It to describe the technical solutions in the embodiments of the present invention more clearly, below will be to embodiment or description of the prior art Needed in attached drawing be briefly described, it should be apparent that, the accompanying drawings in the following description is only of the invention some Embodiment for those of ordinary skill in the art without any creative labor, can also be according to these Attached drawing obtains other attached drawings.
Fig. 1 is the flow chart for the road traffic prediction technique that the embodiment of the present invention one provides;
Fig. 2 is the flow chart of road traffic prediction technique provided by Embodiment 2 of the present invention;
Fig. 3 is the schematic diagram for the server that the embodiment of the present invention three provides;
Fig. 4 is the schematic diagram for the server that the embodiment of the present invention four provides.
Specific embodiment
In being described below, for illustration and not for limitation, the tool of such as particular system structure, technology etc is proposed Body details, to understand thoroughly the embodiment of the present invention.However, it will be clear to one skilled in the art that there is no these specific The present invention also may be implemented in the other embodiments of details.In other situations, it omits to well-known system, device, electricity The detailed description of road and method, in case unnecessary details interferes description of the invention.
In order to illustrate technical solutions according to the invention, the following is a description of specific embodiments.
It is the flow chart for the road traffic prediction technique that the embodiment of the present invention one provides referring to Fig. 1, Fig. 1.In the present embodiment The executing subject of road traffic prediction technique is server.Road traffic prediction technique as shown in the figure may include following step It is rapid:
S101: the vehicle flowrate data in the section to be measured that road monitoring apparatus is sent are obtained, and are in the section to be measured Vehicle in terminal send traveling data.
Current national economy continual high levels increase, and urbanization is unprecedentedly accelerated, automobile role in daily life It is more and more important.However, the abruptly increase of automobile quantity has caused a series of urban transport problems, as Private Traffic tool is spread unchecked directly Connecing leads to that urban highway traffic congestion, traffic accident increase, public transport declines;And social concern, such as motor vehicles play Environmental pollution is serious, resource consumption is excessive caused by increasing etc..The essence of " trip is difficult " problem is transportation system management and control water Flat is relatively low, i.e., city road network structure is unreasonable.These problems seriously restrict the sustainable development in city, or even influence state The normal development of family.Many phenomenon shows urban transport problems already and becomes that government one of must face and solve the problems, such as.
There is the urban road traffic network of oneself in each city, and people are by selecting different routes that can quickly reach The destination of oneself.However, many times due to traffic congestion, if still according to previous traffic path, user will It is difficult to reach the destination of oneself at the appointed time.It is well known that urban road congestion is a kind of dynamic congestion, rather than Static congestion.This also means that the degree of road congestion changes with the variation of time, therefore, the shape of road is obtained State, it is necessary to obtain the traffic flow modes on road.The rise of car networking (Internet of Vehicle, IOV) is derived from Internet of Things The fast development of net (Internet of things, IOT), according to the definition of alliance of Chinese Internet of Things school-run enterprise, IOV, which refers to, to be passed through The electronic equipment on vehicle is loaded in by wireless technology, is realized on information network platform to the quiet multidate information of all vehicles It extracts and efficiently uses, and effectively supervised according to operating status of the different functional requirements to vehicles all in road network Pipe and integrated service, are typical case of the technology of Internet of things in field of transportation system.IOV is in-vehicle network, inter-vehicle network and vehicle-mounted shifting Based on dynamic words networking, according to the communication protocol and Data Exchange Standard of agreement, between vehicle, road, people and internet, carry out The grid of wireless telecommunications and information exchange is the huge Internet being made of information such as vehicle location, speed and routes. At global positioning system (Global Position System, GPS), radio frequency identification, sensor, camera image Devices, the vehicles such as reason can complete the acquisition of itself environment and status information;In the case where there is network communication connection, by mutual Networking technology will monitor the various information Transmission Convergences of vehicle itself to central processing unit;By computer technology, analysis and place Information of vehicles is managed, urban highway traffic is alleviated, it is final to realize the purpose for improving urban road network.
And the appearance of vehicle intelligent terminal (Global trusted Identity, GID), solve dynamic traffic just This problem of information collection.In " end-pipe-cloud " framework of car networking, GID is connected to controller by intelligent vehicle-carried diagnostic system Local area network perceives vehicle static attribute information and dynamic driving behavior information, and analysis in real time is handled, and building is most really and accurately The Internet of Things of dynamic vehicle condition and surrounding enviroment information.GID can be greatly reduced traditional car-mounted terminal investment and network construction at This, solves internet automobile, identity of automobile card and Network Recognition, inherently solves the key problem of car networking terminal.This A little data can pass through vehicle cloud platform long-term preservation.And car owner can pass through the enquiring vehicle operation at any time of mobile phone, client Dynamic and static data information.Traffic congestion results in the huge waste in time resource, and traffic congestion field occurs in traffic In the case where demand approximation or the capacity more than traffic system.It is now it is believed that basic to solve congestion by increasing road Be it is infeasible, the increase for being primarily due to road traffic capacity will lead to the increase of transport need.These factors promote to need to make Traffic congestion is solved the problems, such as with based on the method for information.
Since the road network of main cities is equipped with fairly perfect sensor device and the auxiliary that can extract traffic information Commercial sensor is extracted and analysis different time and traffic data under space and is put into using being possibly realized.In the present embodiment In, the vehicle flowrate data in section to be measured are obtained by road monitoring apparatus, while vehicle is obtained by the terminal in vehicle and is advanced Traveling data in the process.
It should be noted that the road monitoring apparatus in the present embodiment is to be mounted on road both sides or prison elsewhere Equipment, sensor etc. are controlled, for example, such as closed-circuit television camera, GPS device;Terminal in vehicle can be mounted in vehicle On terminal device, such as GPS device etc. be also possible on driver or vehicle passenger and make the terminal device carried with it, for example, Mobile phone, tablet computer etc..Wherein road monitoring apparatus is used for and obtains road conditions, for example, vehicle flowrate data, road deliver feelings Condition etc.;Terminal in vehicle is used to obtain the traveling situation of vehicle, for example, the travel speed of vehicle, dwell time, instantaneous speed The data such as degree, acceleration and current location information.
In practical applications, when the vehicle flowrate data of each crossing monitoring include intersection information, information of vehicles, pass through Between, or the data of the video monitoring from crossing.Vehicle application data are mentioned mainly from such as map quotient, vehicle insurance application program etc. The data service of the third party application of confession includes the information such as user information, longitude and latitude data, speed.Site of road number According to including section, longitude and latitude range data etc..By carrying out Conjoint Analysis and prediction for after these data acquisitions, guarantee The accuracy of road congestion situation prediction.While obtaining the vehicle flowrate data in current section to be measured, pass through the traveling of vehicle Location information in data determines the current position of vehicle, judges whether vehicle is currently traveling on the section to be measured, if, Then obtain the traveling data for operating in the vehicle on the section to be measured.
S102: according to the default road information of the vehicle flowrate data, the traveling data and the section to be measured, meter Calculate the congestion coefficient in the section to be measured.
In the present embodiment, the default road information in section to be measured is stored in advance in the server, wherein default road It include but is not limited to road width, lane quantity, straight length, turn position, turn radian, intersection information in the information of road And traffic lights information etc., herein without limitation.Operation feelings of the vehicle on the road can be determined by default road information Condition, so judge current road segment whether congestion.
After getting vehicle flowrate data and traveling data, according to vehicle flowrate data and traveling data and default road Road information calculates the congestion coefficient in section to be measured.In the present embodiment, vehicle flowrate data are the road vehicle operations of macroscopic view Situation, for example, on road all vehicles average travel speed, for embodying the loading condition and operating condition of road;It advances Data are used to indicate the traveling situation of single unit vehicle, for example, instantaneous velocity, location information etc. that the vehicle is currently advanced.At this In embodiment, the vehicle flowrate data of macroscopic view and single two kinds of data of traveling data are combined, gathering around for section to be measured is calculated Coefficient is filled in, can comprehensively, accurately determine current congestion situation.
S103: determine whether the section to be measured is congestion section according to the congestion coefficient and preset congestion threshold.
In the present embodiment, it is previously provided with congestion threshold, for determining that current congestion coefficient is by congestion threshold It is no excessive, if current congestion coefficient is more than or equal to the congestion threshold, it is determined that current road segment is congestion section, if currently gathering around It fills in coefficient and is less than the congestion threshold, then current road segment is non-congested section.
By determining whether current section to be measured is congestion section, and after judging congestion section, trip is reminded Personnel avoid areas of congestion;Traffic rules can also be formulated for Traffic Administration Bureau researcher and foundation is provided, such as with the lane in which the drivers should pay fees generation For share-car road etc.;Congestion data can also be supplied to city planning design personnel, to planning and designing urban transportation route, than Such as suitably increase section in frequent congestion location;Congestion data can also be supplied to civil engineer, to planning and designing How construction region, such as short-term construction influence traffic.
Above scheme, the vehicle flowrate data in the section to be measured by obtaining road monitoring apparatus transmission, and in described The traveling data that terminal in the vehicle in section to be measured is sent;According to the vehicle flowrate data, traveling data and described The default road information in section to be measured calculates the congestion coefficient in the section to be measured;According to the congestion coefficient and preset gather around Plug threshold value determines whether the section to be measured is congestion section.By the section to be measured for obtaining road monitoring apparatus transmission simultaneously The traveling data of vehicle flowrate data and the vehicle termination on section to be measured, and meter is combined according to vehicle flowrate data and traveling data Calculation obtains congestion coefficient, to judge whether current road segment occurs congestion by congestion coefficient, improves the standard of road congestion judgement True property and integrality, the road traffic control for after provide good data basis.
Referring to fig. 2, Fig. 2 is the flow chart of road traffic prediction technique provided by Embodiment 2 of the present invention.In the present embodiment The executing subject of road traffic prediction technique is server.Road traffic prediction technique as shown in the figure may include following step It is rapid:
S201: the vehicle flowrate data in the section to be measured that road monitoring apparatus is sent are obtained, and are in the section to be measured Vehicle in terminal send traveling data.
The implementation of S101 is identical in S201 embodiment corresponding with Fig. 1 in the present embodiment, specifically refers to The associated description of S101 in the corresponding embodiment of Fig. 1, details are not described herein.
S202: the data that preset requirement is not met in the vehicle flowrate data and the traveling data are deleted.
In the vehicle flowrate data and section to be measured for passing through while obtaining the section to be measured of road monitoring apparatus transmission After the traveling data of vehicle termination, since the data acquisition target of various devices is numerous, vehicle traveling data and vehicle flowrate number There is also the data informations of many types in, and therefore, data volume obtained in step S201 is larger and data type is more, It is then likely to occur more redundant data, these data do not have great use, if being added in the calculating of congestion coefficient, It may influence the judging result of entire congestion situation.Therefore in the present solution, judgement does not meet preset requirement according to preset requirement Data, and it is deleted.
After getting section data, the segment data that can satisfy the need is cleaned, with guarantee data consistency, effectively Property, reasonability.Each parameter has certain value range, such as car speed, and maximum value is no more than place road Limit speed, minimum value 0.If the car speed of the sample data of processing has exceeded this range, it may be considered that the sample Notebook data is abnormal data, needs to delete or correct.The speed of negative value is apparent mistake, can use 0 in data handling Instead of these negative values.Therefore, threshold detection method is exactly to determine parameter according to statistical law to the single traffic information of acquisition Bound, and as benchmark, if traffic information not in the range, determines the traffic information for exception information.Algorithm Think that traffic flow parameter value is certain in a reasonable range in specific time interval.According to this rule, can sentence The fixed traffic parameter not within the scope of this is incorrect data.
Further, may include: in step S202
S2021: the data for not meeting the preset requirement for exercising duration are deleted;It is described to exercise the default of duration It is required that are as follows:Wherein, t (s) is for indicating the enforcement duration;CtFor indicating described The traveling duration correction factor of vehicle in section to be measured;leWhen for indicating the average waiting of vehicle in the section to be measured It is long, τmaxFor indicating red signal duration in the section to be measured or in the delay duration of intersection;cmaxFor indicating The passage coefficient in the section to be measured;vmaxFor indicating the vehicle maximum travelling speed on the preset section to be measured.
In the present embodiment, preset data include but is not limited to the traveling time scale modification system of the vehicle in section to be measured Red signal duration in section several, to be measured or the passage coefficient, described to be measured in the delay duration of intersection, section to be measured Vehicle maximum travelling speed on section.Wherein, the traveling duration correction factor of the vehicle in section to be measured is used for getting Vehicle exercise duration be modified, reduce exercise duration calculating error;Red signal duration in section to be measured is used for table Before showing according to the red lights of the traffic lights in the section to be measured, green light, the holding duration of amber light, the delay duration of intersection The default or estimation of delay duration of the data to vehicle on section to be measured, the passage coefficient in section to be measured are used to indicate current The load traffic capacity on the moment section;Vehicle maximum travelling speed on section to be measured is the maximum limit on the section Speed.By according to above default value, and vehicle in vehicle passes through in current section to be measured enforcement duration, section to be measured Average waiting duration calculation current road segment on enforcement duration upper limit value and lower limit value.According to the upper limit value calculated and Lower limit value screens the data got, determines and is more than or equal to the lower limit value, and is less than or equal to the upper limit The enforcement duration of value exercises duration as reasonable, and is put into the calculating of congestion parameter.
S2022: the data for not meeting the preset requirement of the instantaneous velocity are deleted;The instantaneous velocity is preset It is required that are as follows: 0≤vd≤cv·vmax;Wherein, vdFor indicating the instantaneous velocity, cvFor indicating the vehicle in the section to be measured Speed correction factor.
In the present embodiment, car speed correction factor passes through for being modified to the vehicle instantaneous velocity got Car speed correction factor and the maximum upper limit exercised speedometer and calculate vehicle instantaneous velocity, the vehicle that will be greater than the upper limit are instantaneous Speed is deleted, and normal vehicle running velocity is obtained.Pass through the running time of a vehicle will acquire on certain section of road It is deleted according to the road conditions of present road, guarantees the reliability of running time.
S203: according to the default road information of the vehicle flowrate data and the section to be measured, the section to be measured is calculated Vehicle closeness.
According to vehicle flowrate data, vehicle application data and the site of road data in the data of section, wherein site of road Data include the data such as road number, longitude and latitude.Each in the corresponding section of each road number is calculated according to these data The transit time and wagon flow metric density of vehicle, to determine whether current road segment is congestion section.It is obtained by each monitoring device The vehicle flowrate data arrived, determine current time, the vehicle fleet size n on the preset unit length sectionu, to determine current time Vehicle concentration: pu=nu/du
Execution synchronous with step S203, further include step S204:
S204: it according to the default road information of the traveling data and the section to be measured, calculates the vehicle and passes through institute Passage duration needed for stating section to be measured.
While calculating vehicle closeness, according to the present speed v in vehicle application datad, calculate in preset list Bit length duSection on passage duration: tu=du/vd
It should be noted that needing to monitor different in width, length and different shape in the present embodiment, in monitoring system Road, in order to guarantee uniformity that road information compares, during calculating instant running time in preset unit length, in advance If length immobilize.
S205: pass through formula Ju=α tu+βpuCalculate the congestion coefficient in the section to be measured;Wherein, α, β are for indicating logical The adjusting parameter of row time and concentration;pu、tuIt is respectively used to indicate the vehicle concentration and the current duration.
According to vehicle flowrate data, vehicle application data and the site of road data in the data of section, wherein site of road Data include the data such as road number, longitude and latitude.Each in the corresponding section of each road number is calculated according to these data The transit time and wagon flow metric density of vehicle, to determine whether current road segment is congestion section.According to transit time and intensive journey Spend the congestion coefficient for determining current road segment are as follows:
Ju=α tu+βpu=α du/vd+βnu/du
Wherein, α, β are used to indicate the adjusting parameter of transit time and concentration.It, will after calculating congestion coefficient The coefficient is compared with preset congestion threshold, if congestion coefficient is more than or equal to congestion threshold, it is determined that current road segment For congestion section.
S206: determine whether the section to be measured is congestion section according to the congestion coefficient and preset congestion threshold.
The implementation of S103 is identical in S206 embodiment corresponding with Fig. 1 in the present embodiment, specifically refers to The associated description of S103 in the corresponding embodiment of Fig. 1, details are not described herein.
After step S206, can also include:
If the section to be measured is the congestion section, according to the vehicle application data and the vehicle flowrate data into Row prediction obtains the congestion duration in the section to be measured and the section mark in congestion section;
The section in the congestion duration and the congestion section is identified to the terminal being sent in the vehicle.
Specifically, after judging that current road segment is congestion section, according to vehicle flowrate data and vehicle application data, meter The average speed within preset time period is calculated, and is identified according to the section in the average speed prediction congestion duration and congestion section, Then the section in the congestion duration and the congestion section is identified to the terminal being sent in the vehicle.Judging congestion After section, administrative staff is reminded out to avoid areas of congestion, allows driver according to current congestion situation or other sections Congestion situation determines suitable travelling route, guarantees the efficiency of traffic trip;Traffic can also be formulated for Traffic Administration Bureau researcher Rule provides foundation, such as replaces share-car road etc. with the lane in which the drivers should pay fees;Congestion data can also be supplied to city planning design people Member, suitably increases section etc. to planning and designing urban transportation route, such as in frequent congestion location;It can also be by congestion data It is supplied to civil engineer, to planning and designing construction region, such as how short-term construction influences traffic.
Illustratively, predicting transit time can be by the way of time series.Specifically, being to count certain The numerical value of index, is in chronological sequence sequentially discharged to and is formed by ordered series of numbers.Time series is exactly the Vehicle Speed that will acquire, It is in chronological sequence sequentially discharged to and is formed by ordered series of numbers.By establishment and analysis time sequence, reflected according to time series Development process, direction and trend, analogized or extended, so as to the level that is likely to be breached for a period of time under prediction, and worked as The Persistent Congestion time of preceding congestion state.
Above scheme, by passing through the default road information according to the vehicle flowrate data and the section to be measured got, Calculate the vehicle closeness in section to be measured;According to the default road information of the traveling data and section to be measured that get, vehicle is calculated By passage duration needed for section to be measured, vehicle closeness and the current duration are combined and calculate section to be measured Congestion coefficient finally determines whether section to be measured is congestion section according to congestion coefficient and preset congestion threshold.And in determination Congestion duration and congestion section mark are predicted after congestion section, while these congestion informations being sent to the vehicle in corresponding road section Terminal guarantees the effect of traffic trip so that driver can determine suitable travelling route according to current section congestion situation Rate.This programme carries out Conjoint Analysis and prediction by obtaining road data in real time, is guaranteeing that different kinds of roads traffic can be coped with In the case where random time, improve road congestion situation prediction accuracy, it is ensured that control of traffic and road regulation uniformity and Real-time.
It is a kind of schematic diagram for server that the embodiment of the present invention three provides referring to Fig. 3, Fig. 3.Each list that server includes Member is for executing each step in the corresponding embodiment of FIG. 1 to FIG. 2.Referring specifically in the corresponding embodiment of FIG. 1 to FIG. 2 Associated description.For ease of description, only the parts related to this embodiment are shown.The server 300 of the present embodiment includes:
Acquiring unit 301, the vehicle flowrate data in the section to be measured for obtaining road monitoring apparatus transmission, and it is in institute State the traveling data that the terminal in the vehicle in section to be measured is sent;
Computing unit 302, for according to the default of the vehicle flowrate data, the traveling data and the section to be measured Road information calculates the congestion coefficient in the section to be measured;
Judging unit 303, for whether determining the section to be measured according to the congestion coefficient and preset congestion threshold For congestion section.
Further, the server 300 can also include:
Unit is deleted, the vehicle flowrate data in the section to be measured for obtaining road monitoring apparatus transmission, and in described After the traveling data that terminal in the vehicle in section to be measured is sent, to not being inconsistent in the vehicle flowrate data and the traveling data The data for closing preset requirement are deleted.
Further, the unit of deleting may include:
The data for not meeting the preset requirement for exercising duration are deleted;The preset requirement for exercising duration Are as follows:Wherein, t (s) is for indicating the enforcement duration;CtFor indicating described to be measured The traveling duration correction factor of vehicle in section;leFor indicating the average waiting duration of vehicle in the section to be measured, τmax For indicating red signal duration in the section to be measured or in the delay duration of intersection;cmaxFor indicate it is described to Survey the passage coefficient in section;vmaxFor indicating the vehicle maximum travelling speed on the preset section to be measured;
The data for not meeting the preset requirement of the instantaneous velocity are deleted;The preset requirement of the instantaneous velocity Are as follows: 0≤vd≤cv·vmax;Wherein, vdFor indicating the instantaneous velocity, cvFor indicating the speed of the vehicle in the section to be measured Spend correction factor.
Further, the computing unit 302 can also include:
Closeness computing unit, for the default road information according to the vehicle flowrate data and the section to be measured, meter Calculate the vehicle closeness in the section to be measured;
Current duration calculation unit, for the default road information according to the traveling data and the section to be measured, meter It calculates the vehicle and passes through passage duration needed for the section to be measured;
Congestion coefficient calculation unit, for passing through formula Ju=α tu+βpuCalculate the congestion coefficient in the section to be measured;Its In, α, β are used to indicate the adjusting parameter of transit time and concentration;pu、tuBe respectively used to indicate the vehicle concentration and The current duration.
Further, the server 300 can also include:
Duration prediction unit judges the section to be measured according to the congestion coefficient and preset congestion threshold for described After whether being congestion section, if the section to be measured is the congestion section, according to vehicle application data and described Vehicle flowrate data are predicted, the congestion duration in the section to be measured and the section mark in congestion section are obtained;
Message sending unit, for the section in the congestion duration and congestion section mark to be sent to the vehicle In terminal.
Above scheme, the vehicle flowrate data in the section to be measured by obtaining road monitoring apparatus transmission, and in be measured The traveling data that terminal in the vehicle in section is sent;According to vehicle flowrate data, traveling data and the default road in section to be measured Road information calculates the congestion coefficient in section to be measured;According to congestion coefficient and preset congestion threshold determine section to be measured whether be Congestion section.The vehicle in vehicle flowrate data and section to be measured by obtaining the section to be measured of road monitoring apparatus transmission simultaneously The traveling data of terminal, and combined according to vehicle flowrate data and traveling data and congestion coefficient is calculated, to pass through congestion system Number judges whether current road segment occurs congestion, improves the accuracy and integrality of road congestion judgement, and the road after being is handed over Siphunculus control provides good data basis.
Fig. 4 is the schematic diagram for the server that the embodiment of the present invention four provides.As shown in figure 4, the server 4 of the embodiment wraps It includes: processor 40, memory 41 and being stored in the computer that can be run in the memory 41 and on the processor 40 Program 42.The processor 40 realizes the step in above-mentioned road traffic prediction technique embodiment when executing the computer program 42 Suddenly, such as step 101 shown in FIG. 1 is to 103.Alternatively, the processor 40 realized when executing the computer program 42 it is above-mentioned The function of each module/unit in each Installation practice, such as the function of unit 301 to 303 shown in Fig. 3.
Illustratively, the computer program 42 can be divided into one or more module/units, it is one or Multiple module/units are stored in the memory 41, and are executed by the processor 40, to complete the present invention.Described one A or multiple module/units can be the series of computation machine program instruction section that can complete specific function, which is used for Implementation procedure of the computer program 42 in the server 4 is described.
The server 4 can be desktop PC, notebook, palm PC and cloud server etc. and calculate equipment. The server may include, but be not limited only to, processor 40, memory 41.It will be understood by those skilled in the art that Fig. 4 is only It is the example of server 4, does not constitute the restriction to server 4, may include than illustrating more or fewer components or group Close certain components or different components, for example, the server can also include input-output equipment, network access equipment, Bus etc..
Alleged processor 40 can be central processing unit (Central Processing Unit, CPU), can also be Other general processors, digital signal processor (Digital Signal Processor, DSP), specific integrated circuit (Application Specific Integrated Circuit, ASIC), ready-made programmable gate array (Field- Programmable Gate Array, FPGA) either other programmable logic device, discrete gate or transistor logic, Discrete hardware components etc..General processor can be microprocessor or the processor is also possible to any conventional processor Deng.
The memory 41 can be the internal storage unit of the server 4, such as the hard disk or memory of server 4. The memory 41 is also possible to the External memory equipment of the server 4, such as the plug-in type being equipped on the server 4 is hard Disk, intelligent memory card (Smart Media Card, SMC), secure digital (Secure Digital, SD) card, flash card (Flash Card, FC) etc..Further, the memory 41 can also both include the internal storage unit of the server 4 It also include External memory equipment.The memory 41 is for storing needed for the computer program and the server other Program and data.The memory 41 can be also used for temporarily storing the data that has exported or will export.
It is apparent to those skilled in the art that for convenience of description and succinctly, only with above-mentioned each function Can unit, module division progress for example, in practical application, can according to need and by above-mentioned function distribution by different Functional unit, module are completed, i.e., the internal structure of described device is divided into different functional unit or module, more than completing The all or part of function of description.Each functional unit in embodiment, module can integrate in one processing unit, can also To be that each unit physically exists alone, can also be integrated in one unit with two or more units, it is above-mentioned integrated Unit both can take the form of hardware realization, can also realize in the form of software functional units.In addition, each function list Member, the specific name of module are also only for convenience of distinguishing each other, the protection scope being not intended to limit this application.Above system The specific work process of middle unit, module, can refer to corresponding processes in the foregoing method embodiment, and details are not described herein.
In the above-described embodiments, it all emphasizes particularly on different fields to the description of each embodiment, is not described in detail or remembers in some embodiment The part of load may refer to the associated description of other embodiments.
The unit as illustrated by the separation member may or may not be physically separated, aobvious as unit The component shown may or may not be physical unit, it can and it is in one place, or may be distributed over multiple In network unit.It can select some or all of unit therein according to the actual needs to realize the mesh of this embodiment scheme 's.
If the integrated module/unit be realized in the form of SFU software functional unit and as independent product sale or In use, can store in a computer readable storage medium.Based on this understanding, the present invention realizes above-mentioned implementation All or part of the process in example method, can also instruct relevant hardware to complete, the meter by computer program Calculation machine program can be stored in a computer readable storage medium.
Embodiment described above is merely illustrative of the technical solution of the present invention, rather than its limitations;Although referring to aforementioned reality Applying example, invention is explained in detail, those skilled in the art should understand that: it still can be to aforementioned each Technical solution documented by embodiment is modified or equivalent replacement of some of the technical features;And these are modified Or replacement, the spirit and scope for technical solution of various embodiments of the present invention that it does not separate the essence of the corresponding technical solution should all It is included within protection scope of the present invention.

Claims (10)

1. a kind of road traffic prediction technique characterized by comprising
The vehicle flowrate data in the section to be measured that road monitoring apparatus is sent are obtained, and in the vehicle in the section to be measured The traveling data that terminal is sent;
According to the default road information of the vehicle flowrate data, the traveling data and the section to be measured, calculate it is described to Survey the congestion coefficient in section;
Determine whether the section to be measured is congestion section according to the congestion coefficient and preset congestion threshold.
2. road traffic prediction technique as described in claim 1, which is characterized in that described to obtain what road monitoring apparatus was sent After the traveling data that terminal in the vehicle flowrate data in section to be measured, and the vehicle in the section to be measured is sent, also Include:
The data that preset requirement is not met in the vehicle flowrate data and the traveling data are deleted.
3. road traffic prediction technique as claimed in claim 2, which is characterized in that include each institute in the vehicle flowrate data Vehicle is stated by the traveling duration in the section to be measured, includes the instantaneous velocity of each vehicle in the traveling data;Institute It states and the data for not meeting preset requirement in the vehicle flowrate data and the traveling data is deleted, comprising:
The data for not meeting the preset requirement for exercising duration are deleted;The preset requirement for exercising duration are as follows:Wherein, t (s) is for indicating the enforcement duration;CtFor indicating the section to be measured In vehicle traveling duration correction factor;leFor indicating the average waiting duration of vehicle in the section to be measured, τmaxFor Indicate the red signal duration in the section to be measured or the delay duration in intersection;cmaxFor indicating the road to be measured The passage coefficient of section;vmaxFor indicating the vehicle maximum travelling speed on the preset section to be measured;
The data for not meeting the preset requirement of the instantaneous velocity are deleted;The preset requirement of the instantaneous velocity are as follows: 0≤ vd≤cv·vmax;Wherein, vdFor indicating the instantaneous velocity, cvFor indicating that the car speed in the section to be measured is corrected Coefficient.
4. road traffic prediction technique as described in any one of claims 1-3, which is characterized in that described according to the vehicle flowrate The default road information of data, the traveling data and the section to be measured calculates the congestion coefficient in the section to be measured, packet It includes:
According to the default road information of the vehicle flowrate data and the section to be measured, the vehicle for calculating the section to be measured is intensive Degree;
According to the default road information of the traveling data and the section to be measured, calculates the vehicle and pass through the section to be measured Required passage duration;
Pass through formula Ju=α tu+βpuCalculate the congestion coefficient in the section to be measured;Wherein, α, β are for indicating transit time and close The adjusting parameter of collection degree;pu、tuIt is respectively used to indicate the vehicle concentration and the current duration.
5. road traffic prediction technique as described in claim 1, which is characterized in that described according to the congestion coefficient and default Congestion threshold determine whether the section to be measured is congestion section after, further includes:
If the section to be measured is the congestion section, carried out according to the vehicle application data and the vehicle flowrate data pre- It surveys, obtains the congestion duration in the section to be measured and the section mark in congestion section;
The section in the congestion duration and the congestion section is identified to the terminal being sent in the vehicle.
6. a kind of server, which is characterized in that including memory and processor, being stored in the memory can be at the place The computer program run on reason device, which is characterized in that when the processor executes the computer program, realize following step It is rapid:
The vehicle flowrate data in the section to be measured that road monitoring apparatus is sent are obtained, and in the vehicle in the section to be measured The traveling data that terminal is sent;
According to the default road information of the vehicle flowrate data, the traveling data and the section to be measured, calculate it is described to Survey the congestion coefficient in section;
Determine whether the section to be measured is congestion section according to the congestion coefficient and preset congestion threshold.
7. server as claimed in claim 6, which is characterized in that the section to be measured for obtaining road monitoring apparatus transmission After the traveling data that terminal in vehicle flowrate data, and the vehicle in the section to be measured is sent, further includes:
The data that preset requirement is not met in the vehicle flowrate data and the traveling data are deleted.
8. server as claimed in claim 7, which is characterized in that include that each vehicle passes through in the vehicle flowrate data The traveling duration in the section to be measured includes the instantaneous velocity of each vehicle in the traveling data;It is described to the vehicle The data that preset requirement is not met in data on flows and the traveling data are deleted, comprising:
The data for not meeting the preset requirement for exercising duration are deleted;The preset requirement for exercising duration are as follows:Wherein, t (s) is for indicating the enforcement duration;CtFor indicating the section to be measured In vehicle traveling duration correction factor;leFor indicating the average waiting duration of vehicle in the section to be measured, τmaxFor Indicate the red signal duration in the section to be measured or the delay duration in intersection;cmaxFor indicating the road to be measured The passage coefficient of section;vmaxFor indicating the vehicle maximum travelling speed on the preset section to be measured;
The data for not meeting the preset requirement of the instantaneous velocity are deleted;The preset requirement of the instantaneous velocity are as follows: 0≤ vd≤cv·vmax;Wherein, vdFor indicating the instantaneous velocity, cvFor indicating that the car speed in the section to be measured is corrected Coefficient.
9. such as the described in any item servers of claim 6-8, which is characterized in that it is described according to the vehicle flowrate data, it is described The default road information in traveling data and the section to be measured calculates the congestion coefficient in the section to be measured, comprising:
According to the default road information of the vehicle flowrate data and the section to be measured, the vehicle for calculating the section to be measured is intensive Degree;
According to the default road information of the traveling data and the section to be measured, calculates the vehicle and pass through the section to be measured Required passage duration;
Pass through formula Ju=α tu+βpuCalculate the congestion coefficient in the section to be measured;Wherein, α, β are for indicating transit time and close The adjusting parameter of collection degree;pu、tuIt is respectively used to indicate the vehicle concentration and the current duration.
10. a kind of computer readable storage medium, the computer-readable recording medium storage has computer program, and feature exists In when the computer program is executed by processor the step of any one of such as claim 1 to 5 of realization the method.
CN201811181962.6A 2018-10-11 2018-10-11 Road traffic prediction technique and server Pending CN109360416A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201811181962.6A CN109360416A (en) 2018-10-11 2018-10-11 Road traffic prediction technique and server

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201811181962.6A CN109360416A (en) 2018-10-11 2018-10-11 Road traffic prediction technique and server

Publications (1)

Publication Number Publication Date
CN109360416A true CN109360416A (en) 2019-02-19

Family

ID=65349108

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201811181962.6A Pending CN109360416A (en) 2018-10-11 2018-10-11 Road traffic prediction technique and server

Country Status (1)

Country Link
CN (1) CN109360416A (en)

Cited By (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN109993969A (en) * 2019-03-08 2019-07-09 腾讯大地通途(北京)科技有限公司 A kind of road conditions determine information acquisition method, device and equipment
CN110047276A (en) * 2019-03-11 2019-07-23 广州文远知行科技有限公司 The congestion status of barrier vehicle determines method, apparatus and Related product
CN110164130A (en) * 2019-04-29 2019-08-23 北京北大千方科技有限公司 Traffic incidents detection method, apparatus, equipment and storage medium
CN111681327A (en) * 2020-05-28 2020-09-18 中国联合网络通信集团有限公司 Road charging standard regulation and control method and device
CN111866941A (en) * 2019-04-23 2020-10-30 华为技术有限公司 Network resource scheduling method and related equipment
CN112584345A (en) * 2019-09-27 2021-03-30 大陆汽车系统公司 Device and method for vehicle-to-outside information interactive communication
CN112735147A (en) * 2019-10-29 2021-04-30 北京百度网讯科技有限公司 Method and device for acquiring delay index data of road intersection
CN114282943A (en) * 2021-12-23 2022-04-05 智道网联科技(北京)有限公司 Flow data processing method, processing system, processing device and electronic equipment
CN117177178A (en) * 2023-11-03 2023-12-05 四川川西数据产业有限公司 Urban road distribution system based on Internet of things

Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP5115542B2 (en) * 2009-12-01 2013-01-09 住友電気工業株式会社 Traffic information calculation device, traffic system, and computer program
CN102968901A (en) * 2012-11-30 2013-03-13 青岛海信网络科技股份有限公司 Method for acquiring regional congestion information and regional congestion analyzing device
CN103593976A (en) * 2013-11-28 2014-02-19 青岛海信网络科技股份有限公司 Road traffic state determining method and system based on detector
CN104778834A (en) * 2015-01-23 2015-07-15 哈尔滨工业大学 Urban road traffic jam judging method based on vehicle GPS data
CN108320506A (en) * 2018-02-05 2018-07-24 青岛大学 A kind of discovery method of the congestion period based on composite network

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP5115542B2 (en) * 2009-12-01 2013-01-09 住友電気工業株式会社 Traffic information calculation device, traffic system, and computer program
CN102968901A (en) * 2012-11-30 2013-03-13 青岛海信网络科技股份有限公司 Method for acquiring regional congestion information and regional congestion analyzing device
CN103593976A (en) * 2013-11-28 2014-02-19 青岛海信网络科技股份有限公司 Road traffic state determining method and system based on detector
CN104778834A (en) * 2015-01-23 2015-07-15 哈尔滨工业大学 Urban road traffic jam judging method based on vehicle GPS data
CN108320506A (en) * 2018-02-05 2018-07-24 青岛大学 A kind of discovery method of the congestion period based on composite network

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
邹晓芳: "城市快速路交通流故障数据修复方法研究", 《中国优秀硕士学位论文全文数据库 工程科技Ⅱ辑》 *

Cited By (12)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN109993969A (en) * 2019-03-08 2019-07-09 腾讯大地通途(北京)科技有限公司 A kind of road conditions determine information acquisition method, device and equipment
CN110047276A (en) * 2019-03-11 2019-07-23 广州文远知行科技有限公司 The congestion status of barrier vehicle determines method, apparatus and Related product
CN111866941A (en) * 2019-04-23 2020-10-30 华为技术有限公司 Network resource scheduling method and related equipment
CN111866941B (en) * 2019-04-23 2022-09-23 华为云计算技术有限公司 Network resource scheduling method and related equipment
CN110164130A (en) * 2019-04-29 2019-08-23 北京北大千方科技有限公司 Traffic incidents detection method, apparatus, equipment and storage medium
CN110164130B (en) * 2019-04-29 2021-06-15 北京北大千方科技有限公司 Traffic incident detection method, device, equipment and storage medium
CN112584345A (en) * 2019-09-27 2021-03-30 大陆汽车系统公司 Device and method for vehicle-to-outside information interactive communication
CN112735147A (en) * 2019-10-29 2021-04-30 北京百度网讯科技有限公司 Method and device for acquiring delay index data of road intersection
CN111681327A (en) * 2020-05-28 2020-09-18 中国联合网络通信集团有限公司 Road charging standard regulation and control method and device
CN114282943A (en) * 2021-12-23 2022-04-05 智道网联科技(北京)有限公司 Flow data processing method, processing system, processing device and electronic equipment
CN117177178A (en) * 2023-11-03 2023-12-05 四川川西数据产业有限公司 Urban road distribution system based on Internet of things
CN117177178B (en) * 2023-11-03 2024-05-17 四川川西数据产业有限公司 Urban road distribution system based on Internet of things

Similar Documents

Publication Publication Date Title
CN109360416A (en) Road traffic prediction technique and server
US20210407284A1 (en) Vehicle traffic flow prediction method with missing data
Yang et al. Short-term traffic prediction for edge computing-enhanced autonomous and connected cars
CN108053673A (en) A kind of road conditions forecasting procedure, storage medium and server
CN104424812B (en) A kind of public transport arrival time forecasting system and method
Ye et al. A method for driving route predictions based on hidden Markov model
CN105940284B (en) Electric information provider unit and electric information providing method
CN111739299B (en) Sparse-track vehicle queuing length determination method, device, equipment and medium
US20230419823A1 (en) Methods and systems for managing exhaust emission in a smart city based on industrial internet of things
CN107240254A (en) Traffic Forecasting Methodology and terminal device
WO2018177421A1 (en) Method and device for predicting vehicle emergence point
CN111862590A (en) Road condition prediction method, road condition prediction device and storage medium
Ma et al. Evolution regularity mining and gating control method of urban recurrent traffic congestion: a literature review
CN109410576A (en) Road condition analyzing method, apparatus, storage medium and the system of multisource data fusion
CN109920250A (en) Dynamic prediction urban road intelligent traffic administration system method
Habtie et al. Artificial neural network based real-time urban road traffic state estimation framework
CN111914940B (en) Shared vehicle station clustering method, system, device and storage medium
CN115116216A (en) Global cooperative sensing and decision-making method and device based on vehicle-road cloud interface
CN111667689B (en) Method, device and computer device for predicting vehicle travel time
Chen et al. Reconstructing vehicle trajectories on freeways based on motion detection data of connected and automated vehicles
Banerjee et al. An intelligent hybrid scheme for optimizing parking space: A Tabu metaphor and rough set based approach
WO2021185285A1 (en) Map data collection method, apparatus and system
US20230126317A1 (en) System and method for processing vehicle event data for improved journey trace determination
Ding et al. A deep learning based traffic state estimation method for mixed traffic flow environment
US20230153733A1 (en) Generating greenhouse gas emissions estimations associated with logistics contexts using machine learning techniques

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
RJ01 Rejection of invention patent application after publication

Application publication date: 20190219

RJ01 Rejection of invention patent application after publication