CN109785626A - Through street road condition analyzing method based on RFID data - Google Patents
Through street road condition analyzing method based on RFID data Download PDFInfo
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- CN109785626A CN109785626A CN201910125751.9A CN201910125751A CN109785626A CN 109785626 A CN109785626 A CN 109785626A CN 201910125751 A CN201910125751 A CN 201910125751A CN 109785626 A CN109785626 A CN 109785626A
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Abstract
The invention discloses the through street road condition analyzing methods based on RFID data；Including several RFID card reader equipment being set on through street, and it is set to the electronic tag to match on each vehicle with each RFID card reader equipment, road condition analyzing method and step is as follows: first, collected each electronic tag and corresponding vehicle are uploaded to data processing server by the time respectively by each RFID card reader equipment；Data processing server travels each vehicle average speed in section between every two RFID card reader equipment is calculated and is recorded；Finally, the average speed by several vehicles in the same period of every a road section, average speed or the section congestion for analyzing respective stretch are abnormal.The present invention can be realized real-time road under the scene of through street and analyze, and the accuracy rate of through street scene real-time road analysis is high, can be used in various through street real-time road analyses.
Description
Technical field
The present invention relates to traffic analysis technical fields, in particular to the through street road condition analyzing side based on RFID data
Method.
Background technique
In existing real-time road analytical technology, it is based primarily upon video detecting method and based on GPS Floating Car detection side
Method is realized.
Wherein, based on the passenger flow detection method of video, by identification vehicle license plate come analytical calculation real-time road, this method
Precision is higher, but needs often to conserve camera lens, will receive the factor of illumination, rainwater, dust, and influences detection.
And the detection method based on GPS Floating Car, need a large amount of city vehicle installation GPS devices and Real-Time Sharing data.
Many city buses are assembled with GPS device, but bus is mostly based on urban streets, not to through street coverage
Foot；And the acquisition of other sources of vehicle data is difficult larger.
Therefore, it is necessary to be improved to existing real-time road analytical technology, overcome the deficiencies of existing technologies.
Summary of the invention
In view of the above drawbacks of the prior art, the present invention provides the through street road condition analyzing method based on RFID data,
The first purpose of realization is to realize that real-time road is analyzed under the scene of through street, helps through street administrative department to realize actual time safety pipe
Reason, and the accuracy rate of through street scene real-time road analysis is high, can be used in various through street real-time road analyses.
To achieve the above object, the invention discloses the through street road condition analyzing methods based on RFID data, including setting
In several RFID card reader equipment on the through street, and it is set on each vehicle and is set with each RFID card reader
The standby electronic tag to match, the road condition analyzing method include the following steps:
A. each RFID card reader equipment, respectively by collected each electronic tag and the corresponding vehicle
Data processing server is uploaded to by the time；
B. the data processing server is to the road between each vehicle RFID card reader equipment described in every two
The average speed travelled in section is calculated and is recorded, and the calculation formula of the average speed is as follows:
Speed=dis/ (t2-t1)
Wherein: Speed is single sample of each vehicle between the every two adjacent RFID card reader equipment
The average speed travelled on amount section；
The length in single sample size section of the dis between the every two adjacent RFID card reader equipment；
T2 and t1, which is respectively the same electronic tag, to be passed through by two adjacent RFID card readers are collected
Time；
C. corresponding road is analyzed in the bicycle average speed of the same period in each section by several vehicles
The average speed of section or section congestion are abnormal.
It preferably, will be with a road section entrance, outlet, at different driving directions starting point and end each other in the step c
Point；In a measurement period, the average traveling speed of bicycle corresponding to each described electronic labeling information will test
Degree is used as sample；And in numerous samples, the sample data in 90% confidence interval is extracted as effective sample；To all
The effective sample use K mean value (K-Means) clustering procedure, calculate in the measurement period each section each
The average overall travel speed in a direction.
Beneficial effects of the present invention:
The present invention can select different plant capacities (adjustment detecting distance) according to crossing, realize through street road-section average
Speed real-time detection.
The present invention is high in the accuracy rate that through street scene real-time road is analyzed, and can be used in the real-time road in various through streets
In condition analysis.
It is described further below with reference to technical effect of the attached drawing to design of the invention, specific structure and generation, with
It is fully understood from the purpose of the present invention, feature and effect.
Detailed description of the invention
Fig. 1 shows the flow chart of one embodiment of the invention.
Fig. 2 shows the structural schematic diagrams that RFID card readers two adjacent in one embodiment of the invention are set to through street.
Specific embodiment
Embodiment
As depicted in figs. 1 and 2, through street road condition analyzing method one specific embodiment of the invention based on RFID data,
Including several RFID card reader equipment being set on through street, and it is set on each vehicle and is set with each RFID card reader
The standby electronic tag to match, road condition analyzing method and step are as follows:
Collected each electronic tag and corresponding vehicle are passed through the time respectively by a. each RFID card reader equipment
It is uploaded to data processing server；
B. data processing server travels each vehicle flat in section between every two RFID card reader equipment
Equal speed is calculated and is recorded, and the calculation formula of average speed is as follows:
Speed=dis/ (t2-t1)
Wherein: Speed is each vehicle on single sample size section between every two adjacent RFID card reader equipment
The average speed of traveling；
The length in single sample size section of the dis between every two adjacent RFID card reader equipment；
T2 and t1, which is respectively the same electronic tag, passes through the time by two adjacent RFID card readers are collected；
C. being averaged for respective stretch is analyzed in the bicycle average speed of the same period of every a road section by several vehicles
Speed or section congestion are abnormal.
In certain embodiments, in step c, will with a road section entrance, outlet, different driving directions each other starting point and
Terminal；In a measurement period, the average overall travel speed of bicycle corresponding to each electronic labeling information will test
As sample；And in numerous samples, the sample data in 90% confidence interval is extracted as effective sample；To all effective
Sample uses K mean value (K-Means) clustering procedure, and it is fast to calculate average traveling of every a road section in each direction in measurement period
Degree.
The preferred embodiment of the present invention has been described in detail above.It should be appreciated that those skilled in the art without
It needs creative work according to the present invention can conceive and makes many modifications and variations.Therefore, all technologies in the art
Personnel are available by logical analysis, reasoning, or a limited experiment on the basis of existing technology under this invention's idea
Technical solution, all should be within the scope of protection determined by the claims.
Claims (2)
1. the through street road condition analyzing method based on RFID data；If it is characterised in that it includes being set on the through street
Dry RFID card reader equipment, and it is set to the electronic tag to match on each vehicle with each RFID card reader equipment,
The road condition analyzing method and step is as follows:
A. each RFID card reader equipment, respectively by collected each electronic tag and the corresponding vehicle
Data processing server is uploaded to by the time；
B. the data processing server is in the section between each vehicle RFID card reader equipment described in every two
The average speed of traveling is calculated and is recorded, and the calculation formula of the average speed is as follows:
Speed=dis/ (t2-t1)
Wherein: Speed is single sample size road of each vehicle between the every two adjacent RFID card reader equipment
The average speed travelled in section；
The length in single sample size section of the dis between the every two adjacent RFID card reader equipment；
T2 and t1, which is respectively the same electronic tag, passes through the time by two adjacent RFID card readers are collected；
C. respective stretch is analyzed in the bicycle average speed of the same period in each section by several vehicles
Average speed or section congestion are abnormal.
2. the through street road condition analyzing method according to claim 1 based on RFID data, which is characterized in that in the step
It, will be with a road section entrance, outlet, in different driving directions beginning and end each other in rapid c；In a measurement period, it will examine
The average overall travel speed of bicycle corresponding to each described electronic labeling information is measured as sample；And in numerous samples
In, the sample data in 90% confidence interval is extracted as effective sample；K mean value is used to all effective samples
Clustering procedure calculates average overall travel speed of each section in each direction in the measurement period.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
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| CN201910125751.9A CN109785626A (en) | 2019-02-20 | 2019-02-20 | Through street road condition analyzing method based on RFID data |
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| Application Number | Priority Date | Filing Date | Title |
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| CN201910125751.9A CN109785626A (en) | 2019-02-20 | 2019-02-20 | Through street road condition analyzing method based on RFID data |
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| CN109785626A true CN109785626A (en) | 2019-05-21 |
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| CN201910125751.9A Pending CN109785626A (en) | 2019-02-20 | 2019-02-20 | Through street road condition analyzing method based on RFID data |
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Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102226932A (en) * | 2011-05-31 | 2011-10-26 | 东北大学 | Vehicle speed measuring method based on radio frequency identification technology |
| CN104318781A (en) * | 2014-10-27 | 2015-01-28 | 东南大学 | RFID technology based travel speed obtaining method |
| KR20160065339A (en) * | 2014-11-28 | 2016-06-09 | 한국도로공사 | Portable roadway detector evaluation system and monitoring system |
| CN105872959A (en) * | 2016-05-12 | 2016-08-17 | 西安电子科技大学 | Automatic sensing method for urban road condition based on mobile adaptive clustering |
| CN106023592A (en) * | 2016-07-11 | 2016-10-12 | 南京邮电大学 | Traffic jam detection method based on GPS data |
| CN106856050A (en) * | 2015-12-08 | 2017-06-16 | 哈尔滨大通瑞持网络有限公司 | A kind of preparation method of express highway intelligent safety management system |
-
2019
- 2019-02-20 CN CN201910125751.9A patent/CN109785626A/en active Pending
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102226932A (en) * | 2011-05-31 | 2011-10-26 | 东北大学 | Vehicle speed measuring method based on radio frequency identification technology |
| CN104318781A (en) * | 2014-10-27 | 2015-01-28 | 东南大学 | RFID technology based travel speed obtaining method |
| KR20160065339A (en) * | 2014-11-28 | 2016-06-09 | 한국도로공사 | Portable roadway detector evaluation system and monitoring system |
| CN106856050A (en) * | 2015-12-08 | 2017-06-16 | 哈尔滨大通瑞持网络有限公司 | A kind of preparation method of express highway intelligent safety management system |
| CN105872959A (en) * | 2016-05-12 | 2016-08-17 | 西安电子科技大学 | Automatic sensing method for urban road condition based on mobile adaptive clustering |
| CN106023592A (en) * | 2016-07-11 | 2016-10-12 | 南京邮电大学 | Traffic jam detection method based on GPS data |
Non-Patent Citations (1)
| Title |
|---|
| 丁宏飞: "城市快速路交通信息提取与协同优化研究", 《中国博士学位论文全文数据库 工程科技II辑》 * |
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