CN109285347A - A kind of urban road congestion analysis system based on cloud platform - Google Patents
A kind of urban road congestion analysis system based on cloud platform Download PDFInfo
- Publication number
- CN109285347A CN109285347A CN201811127009.3A CN201811127009A CN109285347A CN 109285347 A CN109285347 A CN 109285347A CN 201811127009 A CN201811127009 A CN 201811127009A CN 109285347 A CN109285347 A CN 109285347A
- Authority
- CN
- China
- Prior art keywords
- road
- key
- city
- network
- combination
- 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
Links
Classifications
-
- 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
-
- 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
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
- H04L41/12—Discovery or management of network topologies
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/10—Protocols in which an application is distributed across nodes in the network
Abstract
The present invention provides a kind of urban road congestion analysis system based on cloud platform, it include: cloud server, the cloud server further comprises: city road network database, key road segment labeling module, data transmission module and road condition analyzing module, wherein, city road network database, city road network data are provided, the road net data includes urban road network topological diagram；Key road segment labeling module marks key road segment from city road network data；Data transmission module, for obtaining the real time road information of key road segment；Road condition analyzing module carries out jamming analysis to the key road segment of mark, the road information of key road segment and the road information threshold value prestored is compared, generates jamming analysis as a result, sending management terminal for jamming analysis result；Management terminal, for receiving the jamming analysis result and being shown.The present invention analyzes the jam situation of road according to the road information of acquisition, automatically generates analysis as a result, intelligent level is high.
Description
Technical field
The urban road congestion analysis system based on cloud platform that the present invention relates to a kind of.
Background technique
Currently, the great rising of the resident population in city, each main roads in morning and evening city are gathered around with the continuous development in city
Stifled situation is got worse, especially as being increasing for vehicle, in order to ensure the line efficiency out of morning and evening peak period Urban population,
The congestion for solving road is particularly significant for traffic dispersion system carries out scheduling in time.
Summary of the invention
In view of the above-mentioned problems, the present invention is intended to provide a kind of urban road congestion analysis system based on cloud platform.
The purpose of the present invention is realized using following technical scheme:
A kind of urban road congestion analysis system based on cloud platform, comprising:
Cloud server, the cloud server further comprises: city road network database, key road segment labeling module,
Data transmission module and road condition analyzing module, wherein
City road network database, provides city road network data, and the road net data includes urban road network topological diagram；
Key road segment labeling module marks key road segment from city road network data；
Data transmission module, for obtaining the road information of key road segment；
Road condition analyzing module carries out jamming analysis to the key road segment of mark, by the road information of key road segment and prestores
Road information threshold value be compared, generate jamming analysis as a result, sending management terminal for jamming analysis result；
Management terminal, for receiving the jamming analysis result and being shown.
The invention has the benefit that analysis system of the present invention is handled data using cloud server, wherein city
City's Traffic network database provides city road network data for system, makes to analyze closer to reality urban road；Key road segment mark
Module marks the key road segment in city to be further analysed according to city road network, with strong points；Data transmission module obtains road
Real time road information, strong real-time；Road condition analyzing module analyzes the jam situation of road according to the road information of acquisition, automatically
Analysis is generated as a result, and sending the result to management terminal, intelligent level height；Management terminal receives jamming analysis result and goes forward side by side
Row display facilitates the jam situation that manager intuitively, accurately obtains urban road.
Detailed description of the invention
The present invention will be further described with reference to the accompanying drawings, but the embodiment in attached drawing is not constituted to any limit of the invention
System, for those of ordinary skill in the art, without creative efforts, can also obtain according to the following drawings
Other attached drawings.
Fig. 1 is frame construction drawing of the invention.
Appended drawing reference:
Cloud server 1, management terminal 2, road information collector 3, city road network database 11, key road segment mark mould
Block 12, data transmission module 13, road condition analyzing module 14, display module 21, receiving module 22, information issuing module 23
Specific embodiment
In conjunction with following application scenarios, the invention will be further described.
Referring to Fig. 1, a kind of urban road congestion analysis system based on cloud platform is shown, comprising:
Cloud server 1, the cloud server 1 further comprises: city road network database 11, key road segment mark mould
Block 12, data transmission module 13 and road condition analyzing module 14, wherein
City road network database 11, provides city road network data, and the road net data includes urban road network topological diagram；
Key road segment labeling module 12 marks key road segment from city road network data；
Data transmission module 13, for obtaining the real time road information of key road segment；
Road condition analyzing module 14 carries out jamming analysis to the key road segment of mark, by the road information of key road segment and in advance
The road information threshold value deposited is compared, and generates jamming analysis as a result, sending management terminal 2 for jamming analysis result；
Management terminal 2, for receiving the jamming analysis result and being shown.
Above embodiment of the present invention, above embodiment of the present invention are handled data using cloud server 1,
Wherein city road network database 11 provides city road network data for system, makes to analyze closer to reality urban road；It is crucial
Section labeling module 12 marks the key road segment in city to be further analysed according to city road network, with strong points；Data transmit mould
Block 13 obtains the real time road information of road, strong real-time；Road condition analyzing module 14 analyzes road according to the road information of acquisition
Jam situation, automatically generate analysis as a result, and send the result to management terminal 2, intelligent level is high；Management terminal 2 connects
It receives jamming analysis result and is shown, facilitate the jam situation that manager intuitively, accurately obtains urban road.
Preferably, the system also includes: the road information collector 3 of the key road segment is set, for acquire close
The road information on keyway road, and it is transmitted to cloud server 1；Wherein, the road information collector 3 is passed including vehicle flowrate
Sensor, vehicle speed sensor acquire vehicle flowrate, the average speed of key road segment respectively.
Above embodiment of the present invention, by the setting information collector in real road, the road information that will acquire is real
When, directly upload in cloud server 1, be capable of the position of setting information collector according to the actual situation, accurately obtain
Road information accurately analyzes road jam situation for system and lays a good foundation.
Preferably, road information collector 3 is additionally arranged in all roads in city road network, for acquiring the road of road
Road information, and it is transmitted to cloud server 1.
Above embodiment of the present invention, in addition to key road segment, remaining section in city road network is also equipped with information collection
Device can store the information of acquisition into cloud server 1 for acquiring road information, be adjusted when in need when
With.
Preferably, the management terminal 2 further comprises: display module 21, receiving module 22 and information issuing module 23,
Wherein,
Receiving module 22, the jamming analysis result for receiving to be sent by cloud server 1；
Display module 21, for showing the jamming analysis result obtained；
Information issuing module 23, for the jamming analysis result to be published to user terminal.
Above embodiment of the present invention, display module 21 can intuitively be shown in management terminal 2 is given birth to by cloud server 1
At jamming analysis as a result, and by information issuing module 23 by jamming analysis result be published to user terminal (such as traffic management assistant be
The communication terminal etc. that system, traffic police hold), to make corresponding scheduling according to jamming analysis result in time, improve road pipe
The efficiency of reason.
The key road segment labeling module 12, specifically includes:
The criticality scoring for assessing each road in city road network arranges the road by criticality scoring from high to low
Road, the pavement marker by Q% before occupied road sum in sequence is key road segment,
Wherein, the score function that the criticality scoring of each road uses in the assessment city road network are as follows:
In formula, MzIndicate the criticality scoring of road z,Indicate that the vehicle of road z drives into mouth sum,It indicates not
It drives into mouthful period with vehicle to the sum of road z average vehicle flow driven into, H 'zIndicate road z in actual cities road network
Side betweenness in topological diagram, KτIndicate that road z vehicle is driven out to mouth sum,Indicate that different vehicle is driven into mouthful period to road z
The sum of average vehicle flow driven into,And BτThe vehicle for respectively indicating the road z of setting drives into mouth and the weight factor for being driven out to mouth,Indicate the maximum vehicle flowrate that can be dredged of road z, VzIndicate that road z monitors current vehicle flowrate.
Preferably, Q=25%.
In the road network of actual cities, since the scale of city road network is very huge, including road quantity also very
It is huge, but the traffic behavior in the section of some keys can influence the whole traffic conditions of the section section in city road network, because
This is it may be said that the key road segment is in relatively important position in city road network, it is therefore desirable to the traffic shape of the key road segment
Condition is especially analyzed.
Above embodiment of the present invention judges the road to the betweenness of vehicle flowrate and the road in road network according to road
The criticality on road, and metrization is carried out to the criticality of road by criticality scoring and is shown, on this basis into
Key road is chosen in row sequence, and objectivity is strong, and accuracy is high.
The key road labeling module further comprises:
Obtain the key road combination in city road network, by key road combine in include section labeled as critical path
Section；
Wherein, the key road combination in city road network is obtained, further comprises:
By difference road composition road combination any in city road network, the attribute of the different attribute of road combination is obtained
Value, according to the attribute value structure attribute value matrix G=(g of acquisitionxz)1×h；Wherein gxzIndicate the attribute of the attribute z of road combination x
Value, l indicate the quantity of road combination in road network structure, and h indicates the quantity of attribute, wherein the attribute includes in following
It is one or more: betweenness index of the road in city road network in road combination, in road combination road partitioning site in city
Betweenness index, connection scale merit, network failure degree index in road network etc.；Wherein, the connection scale merit indicates city
The variable quantity of maximum network connected region scale after the combination disconnection of road described in road network, the network failure degree index, table
Show after the combination of road described in city road network disconnects and occurs being isolated the quantity of road；
Standardization processing is carried out to the attribute value matrix, obtains standardization attribute value matrix D=(dxz)1×h, wherein
The betweenness ratio between different road combinations is obtained, constitutes betweenness than Matrix C=(cxy)l×l, wherein cxyIndicate road
Betweenness ratio of the x relative to road combination y is combined, whereinWherein u (x) indicates the betweenness of road combination x；Wherein save
The betweenness of point road is weighting betweenness the sum of of the road of composition road combination in city road network；
Obtain the criticality scoring M of road combinationx(w), wherein Mx(w) acquisition function are as follows:
In formula, Mx(w) the criticality scoring of road combination x, w={ w are indicated1, w2..., whIndicate optimization weight sets
It closes, which is obtained by following customized Optimized model:
According to above-mentioned customized Optimized model, customized Optimized model is solved using quadratic programming, obtains each attribute pair
The optimal weights set w answered；
Road composite marking by S% before criticality marking and queuing occupied road combination sum is key road combination.
Preferably, S=25.
In the road network of actual cities, in addition to key road labeling module uses single road judgement side in above embodiment
Outside the key road segment that formula obtains, position of the combination of some roads in key equally in city road network, for example, working as city road
An enclosed region only has two road and is in communication with the outside in net, and the traffic condition in this two road will will affect this closure at this time
The traffic conditions of all roads in region, therefore, when the range of the enclosed region is met certain condition, the two road are in city
It is then similarly in crucial position in city's road network, it should be marked to monitor for key road segment and by system to its congestion, with
Just its congestion is found at the first time and makes corresponding scheduling.
Above embodiment of the present invention obtains crucial road combination first, then by key road combine in section
Labeled as key road segment, road is combined first, and is combined according to road and carries out whole judge, using different indexs
To road combination criticality judge, and by criticality score metrization is carried out to it, on this basis into
Key road combination is chosen in row sequence, accuracy, the adaptability and comprehensive of key road segment mark is further improved, to mention
The high reliability of analysis system.
Preferably, the road condition analyzing module 14, specifically includes: dividing the average speed v obtained from key road segment
Analysis, if the average speed obtained is less than the threshold value V of setting1, then marking the state of the key road segment is congestion；If what is obtained is averaged
Speed is greater than the threshold value V of setting1But it is less than the threshold value V of setting2, wherein V2> V1, then it is slow for marking the state of the key road segment
Slowly；If the average speed obtained is greater than the threshold value V of setting2, then it is normal for marking the state of the key road segment；According to key road segment
State generate jamming analysis result；
Preferably, the road condition analyzing module 14 further comprises: when the state of key road segment be marked as it is normal or slow
When slow, further the vehicle flowrate y of key road segment is analyzed as follows:
Original width is used to handle for the data window of L the vehicle flowrate for obtaining key road segment, when the vehicle flowrate of acquisition
When data number reaches L, which is obtained using least square method to the L status data according to the fitting function model of setting
The fitting function of window, wherein the fitting function model set is N (T)=A (T-T0)+B, the fitting function of acquisition is Wherein n=1,2 ..., L, Δ T indicate to obtain the status data
Time interval, B1Indicate T in fitting function01Moment corresponding value；
It is fitted the vehicle flowrate data of subsequent acquisition using the fitting function of acquisition, and calculates steady coefficient, wherein use
Customized steady coefficient function are as follows:
In formula, P (T1+ I Δ T) indicate T1The steady coefficient of data at+I Δ T moment, N ' (T1+ i Δ T) indicate T1When+i Δ T
The vehicle flowrate data for the practical acquisition carved,Indicate T1The vehicle flowrate number that+i Δ T moment obtains according to fitting function
According to I=L '+1, L ' indicate current data window width；
If steady coefficient is less than the threshold value of setting, expand the width of data window, and continue the state for being fitted subsequent acquisition
Data, and the updated fitting function of output；If steady coefficient is greater than the threshold value of setting, the vehicle flowrate of the data window is exported
Data fitting function, and new data window is used, handle the vehicle flowrate data of subsequent new acquisition；
Road traffic state is assessed according to the slope A of the fitting function of the output, if slope A is greater than setting
Threshold value A1If the state of key road segment is normal at this time, marking the state of the key road segment is slow early warning；If crucial at this time
The state in section be it is slow, then mark the key road segment state be congestion warning；
Jamming analysis result is generated according to the status information of key road.
Above embodiment of the present invention, road condition analyzing module 14 first judge the average speed of key road segment, root
The congestion of road is judged according to average speed；The vehicle flowrate rate of change of key road is detected simultaneously, using data
Window obtains the little data of variable quantity and is focused on, and when the variable quantity of vehicle flowrate changes, can send out at the first time
Now and using new data window vehicle flowrate rate of change is assessed, if vehicle flowrate rate of change is excessive, proves vehicle flowrate
Increasing and issuing warning information, reminding the traffic situation of change in the manager section, adaptable, intelligent level is high.
Finally it should be noted that the above embodiments are merely illustrative of the technical solutions of the present invention, rather than the present invention is protected
The limitation of range is protected, although explaining in detail referring to preferred embodiment to the present invention, those skilled in the art are answered
Work as analysis, it can be with modification or equivalent replacement of the technical solution of the present invention are made, without departing from the reality of technical solution of the present invention
Matter and range.
Claims (5)
1. a kind of urban road congestion analysis system based on cloud platform characterized by comprising
Cloud server, the cloud server further comprises: city road network database, key road segment labeling module, data
Transmission module and road condition analyzing module, wherein
City road network database, provides city road network data, and the road net data includes urban road network topological diagram；
Key road segment labeling module marks key road segment from city road network data；
Data transmission module, for obtaining the real time road information of key road segment；
Road condition analyzing module carries out jamming analysis to the key road segment of mark, by the road information of key road segment and the road prestored
Road information threshold is compared, and generates jamming analysis as a result, sending management terminal for jamming analysis result；
Management terminal, for receiving the jamming analysis result and being shown.
2. a kind of urban road congestion analysis system based on cloud platform according to claim 1, which is characterized in that described
System further include: the road information collector of the key road segment is set, for acquiring the road information of key road, and will
It is transferred to cloud server；Wherein, the road information collector includes magnetic-field Sensor for Traffic Counting, vehicle speed sensor, is adopted respectively
Collect vehicle flowrate, the average speed of key road segment.
3. a kind of urban road congestion analysis system based on cloud platform according to claim 1, which is characterized in that described
Management terminal further comprises: display module, receiving module and information issuing module, wherein
Receiving module, the jamming analysis result for receiving to be sent by cloud server；
Display module, for showing the jamming analysis result obtained；
Information issuing module, for the jamming analysis result to be published to user terminal.
4. a kind of urban road congestion analysis system based on cloud platform according to claim 2, which is characterized in that described
Key road segment labeling module, specifically includes:
The criticality scoring for assessing each road in city road network arranges the road by criticality scoring from high to low,
Pavement marker by Q% before occupied road sum in sequence is key road segment,
Wherein, the score function that the criticality scoring of each road uses in the assessment city road network are as follows:
In formula, MzIndicate the criticality scoring of road z,Indicate that the vehicle of road z drives into mouth sum,Indicate different vehicle
It drives into mouthful period to the sum of road z average vehicle flow driven into, H 'zIndicate road z in actual cities road network topology figure
In side betweenness, KτIndicate that road z vehicle is driven out to mouth sum,It indicates that different vehicle was driven into mouthful period to drive into road z
The sum of average vehicle flow,And BτThe vehicle for respectively indicating the road z of setting drives into mouth and the weight factor for being driven out to mouth,
Indicate the maximum vehicle flowrate that can be dredged of road z, VzIndicate that road z monitors current vehicle flowrate.
5. a kind of urban road congestion analysis system based on cloud platform according to claim 4, which is characterized in that
The key road labeling module further comprises:
Obtain the key road combination in city road network, by key road combine in include section labeled as key road segment；
Wherein, the key road combination in city road network is obtained, further comprises:
By difference road composition road combination any in city road network, the attribute value of the different attribute of road combination, root are obtained
According to the attribute value structure attribute value matrix G=(g of acquisitionxz)l×h；Wherein gxzIndicate the attribute value of the attribute z of road combination x, l table
Show the quantity that road in road network structure combines, h indicates the quantity of attribute, wherein the attribute include one in following or
It is multinomial: betweenness index of the road in city road network in road combination, in road combination road partitioning site in city road network
Betweenness index, connection scale merit, network failure degree index etc.；Wherein, the connection scale merit indicates in city road network
The variable quantity of maximum network connected region scale after the road combination disconnection, the network failure degree index indicate city
The combination of road described in road network occurs being isolated the quantity of road after disconnecting；
Standardization processing is carried out to the attribute value matrix, obtains standardization attribute value matrix D=(dxz)l×h, wherein
The betweenness ratio between different road combinations is obtained, constitutes betweenness than Matrix C=(cxy)l×l, wherein cxyIndicate that road combines x
Relative to the betweenness ratio of road combination y, whereinWherein u (x) indicates the betweenness of road combination x；Wherein node-link
Betweenness be to form weighting betweenness the sum of of the road in city road network of road combination；
Obtain the criticality scoring M of road combinationx(w), wherein Mx(w) acquisition function are as follows:
In formula, Mx(w) the criticality scoring of road combination x, w={ w are indicated1, w2..., whIndicate optimization weight set, it should
Optimize weight set to be obtained by following customized Optimized model:
According to above-mentioned customized Optimized model, customized Optimized model is solved using quadratic programming, it is corresponding to obtain each attribute
Optimal weights set w；
Road composite marking by S% before criticality marking and queuing occupied road combination sum is key road combination.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811127009.3A CN109285347A (en) | 2018-09-26 | 2018-09-26 | A kind of urban road congestion analysis system based on cloud platform |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811127009.3A CN109285347A (en) | 2018-09-26 | 2018-09-26 | A kind of urban road congestion analysis system based on cloud platform |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN109285347A true CN109285347A (en) | 2019-01-29 |
Family
ID=65182395
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201811127009.3A Pending CN109285347A (en) | 2018-09-26 | 2018-09-26 | A kind of urban road congestion analysis system based on cloud platform |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN109285347A (en) |
Cited By (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110853351A (en) * | 2019-11-12 | 2020-02-28 | 华侨大学 | Monitoring system in intelligent road environment |
| CN111710162A (en) * | 2020-07-07 | 2020-09-25 | 深圳市数字城市工程研究中心 | Urban road network traffic operation condition monitoring method and system |
| CN112887896A (en) * | 2019-11-13 | 2021-06-01 | 中移物联网有限公司 | Scenic spot traffic flow statistical method and device and server |
| CN114550443A (en) * | 2022-01-21 | 2022-05-27 | 阿里云计算有限公司 | Road network data processing method, equipment and readable medium |
| CN114613145A (en) * | 2022-05-12 | 2022-06-10 | 中运科技股份有限公司 | Passenger traffic flow perception early warning system and method under big data |
| CN114677843A (en) * | 2022-02-17 | 2022-06-28 | 阿里云计算有限公司 | Road condition information processing method, device and system and electronic equipment |
| CN115457766A (en) * | 2022-08-31 | 2022-12-09 | 华迪计算机集团有限公司 | Method and system for predicting road congestion state |
| CN116797055A (en) * | 2023-08-28 | 2023-09-22 | 日照朝力信息科技有限公司 | Urban road planning method and system based on Internet of things |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102637357A (en) * | 2012-03-27 | 2012-08-15 | 山东大学 | Regional traffic state assessment method |
| CN103700274A (en) * | 2014-01-17 | 2014-04-02 | 重庆大学 | Traffic flow detection induction method |
| US20150206428A1 (en) * | 2014-01-21 | 2015-07-23 | Iteris, Inc. | Estimation of hourly traffic flow profiles using speed data and annual average daily traffic data |
| CN105390000A (en) * | 2015-12-18 | 2016-03-09 | 天津通翔智能交通系统有限公司 | Traffic signal control system and method based on road condition traffic big data |
| CN107248283A (en) * | 2017-07-18 | 2017-10-13 | 北京航空航天大学 | A kind of urban area road network evaluation of running status method of consideration section criticality |
-
2018
- 2018-09-26 CN CN201811127009.3A patent/CN109285347A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102637357A (en) * | 2012-03-27 | 2012-08-15 | 山东大学 | Regional traffic state assessment method |
| CN103700274A (en) * | 2014-01-17 | 2014-04-02 | 重庆大学 | Traffic flow detection induction method |
| US20150206428A1 (en) * | 2014-01-21 | 2015-07-23 | Iteris, Inc. | Estimation of hourly traffic flow profiles using speed data and annual average daily traffic data |
| CN105390000A (en) * | 2015-12-18 | 2016-03-09 | 天津通翔智能交通系统有限公司 | Traffic signal control system and method based on road condition traffic big data |
| CN107248283A (en) * | 2017-07-18 | 2017-10-13 | 北京航空航天大学 | A kind of urban area road network evaluation of running status method of consideration section criticality |
Cited By (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110853351A (en) * | 2019-11-12 | 2020-02-28 | 华侨大学 | Monitoring system in intelligent road environment |
| CN112887896A (en) * | 2019-11-13 | 2021-06-01 | 中移物联网有限公司 | Scenic spot traffic flow statistical method and device and server |
| CN111710162A (en) * | 2020-07-07 | 2020-09-25 | 深圳市数字城市工程研究中心 | Urban road network traffic operation condition monitoring method and system |
| CN111710162B (en) * | 2020-07-07 | 2022-04-01 | 深圳市数字城市工程研究中心 | Urban road network traffic operation condition monitoring method and system |
| CN114550443A (en) * | 2022-01-21 | 2022-05-27 | 阿里云计算有限公司 | Road network data processing method, equipment and readable medium |
| CN114677843A (en) * | 2022-02-17 | 2022-06-28 | 阿里云计算有限公司 | Road condition information processing method, device and system and electronic equipment |
| CN114613145A (en) * | 2022-05-12 | 2022-06-10 | 中运科技股份有限公司 | Passenger traffic flow perception early warning system and method under big data |
| CN115457766A (en) * | 2022-08-31 | 2022-12-09 | 华迪计算机集团有限公司 | Method and system for predicting road congestion state |
| CN115457766B (en) * | 2022-08-31 | 2023-08-08 | 华迪计算机集团有限公司 | Method and system for predicting road congestion state |
| CN116797055A (en) * | 2023-08-28 | 2023-09-22 | 日照朝力信息科技有限公司 | Urban road planning method and system based on Internet of things |
| CN116797055B (en) * | 2023-08-28 | 2023-11-07 | 日照朝力信息科技有限公司 | Urban road planning method and system based on Internet of things |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN109285347A (en) | A kind of urban road congestion analysis system based on cloud platform | |
| CN110533885A (en) | Urban waterlogging monitoring and warning system and method for early warning | |
| CN108109382A (en) | A kind of congestion points based on composite network, congestion line, the discovery method of congestion regions | |
| CN109285376A (en) | A kind of bus passenger flow statistical analysis system based on deep learning | |
| US20170337811A1 (en) | Determination of a Free-Flow Speed for a Link Segment | |
| CN107065743A (en) | A kind of Irrigation District Information System and its management method | |
| CN114093168A (en) | Urban road traffic running state evaluation method based on toughness view angle | |
| CN107634864A (en) | A kind of high-frequency data Real-time Collection transmission method for network of highways level bridge | |
| CN110996259B (en) | Intelligent garbage monitoring and clearing method and device based on edge calculation | |
| CN105512166A (en) | Traffic parallel method with mapping between microblog public sentiments and city road conditions | |
| CN106651027A (en) | Internet regular bus route optimization method based on social network | |
| CN109409713A (en) | Road network appraisal procedure based on Bayesian model and three times standard deviation criterion | |
| CN107071053A (en) | A kind of road ponding monitoring system based on WSAN | |
| CN114550073B (en) | Monitoring system of new energy automobile charging pile | |
| CN106205125A (en) | A kind of ambulance arrival time real-time estimate system and method | |
| CN107607814A (en) | A kind of electric energy quality monitoring system and its monitoring method of distributed power source access | |
| CN106027611A (en) | Data transmission method between agricultural vehicle-mounted intelligent terminal and monitoring client based on WebGIS technology | |
| CN104408919B (en) | A kind of road traffic parameter manual research system based on mobile intelligent terminal | |
| CN108053132A (en) | Bridge defect intelligently pushing system | |
| CN105070058B (en) | A kind of accurate road condition analyzing method and system based on real-time road video | |
| CN114363316A (en) | Intelligent networking monitoring and supervision system for cross-regional road infrastructure | |
| CN115776449A (en) | Train Ethernet communication state monitoring method and system | |
| CN114999180A (en) | Expressway severe weather traffic early warning system and method based on Internet of things | |
| CN113535406A (en) | Intelligent pig farm breeding data processing system and method | |
| CN112686407A (en) | Traffic safety facility digital system based on intelligent network connection |
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: 20190129 |
|
| RJ01 | Rejection of invention patent application after publication |