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Urban road traffic parameter estimation and road situation discrimination method based on RFID (Radio Frequency Identification) data and application system

A traffic parameter and road traffic technology, applied in the field of intelligent transportation, can solve the problems of inability to obtain accurate results, efficiency defects, and low accuracy of extraction results.

Inactive Publication Date: 2014-01-08
TONGJI UNIV
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  • Summary
  • Abstract
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  • Claims
  • Application Information

AI Technical Summary

Benefits of technology

The technical effect of this invention is that it can efficiently eliminate incorrect or valid data from an acquired radio frequency identifier (RFI) dataset for accurate tracking purposes during driving activities by calculating various factors like distance traveled over different sections within a specific area based upon their location along with other variables like velocity and direction. This helps improve safety measures and reduce congestion caused by unexpected events happening around them.

Problems solved by technology

The technical problem addressed by this patented method relates to improving the precision and reliability of detecting various parameters like speed limits or roads along which vehicles move during route planning operations without relying solely upon traditional techniques involving manual input from human operators. This would improve overall performance and reduce costs associated with vehicle navigation services while also providing valuable feedback about changes made over longer periods of use.

Method used

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  • Urban road traffic parameter estimation and road situation discrimination method based on RFID (Radio Frequency Identification) data and application system
  • Urban road traffic parameter estimation and road situation discrimination method based on RFID (Radio Frequency Identification) data and application system
  • Urban road traffic parameter estimation and road situation discrimination method based on RFID (Radio Frequency Identification) data and application system

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Embodiment Construction

[0025] In the use of urban road traffic information collection data, theoretical and practical innovations are carried out from three parts: basic data utilization, data preprocessing and dynamic road condition discrimination, and a stable and reliable real-time processing system has been developed.

[0026] The system is based on the C / S architecture and includes a background computing server and an interface server. The background computing server is responsible for real-time processing and analysis of the input data, combining the GIS spatial database and the RFID point information data table to build a road condition historical characteristic analysis database, so as to convert real-time traffic parameters into road condition judgment results; the interface server passes and The data interface of the RFID detection equipment on the road network writes the detection results of each detector into the database of the computing server in real time.

[0027] The invention takes into...

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Abstract

The invention relates to an urban road traffic parameter estimation and road situation discrimination method based on RFID (Radio Frequency Identification) data and an application system and belongs to the technical field of intelligent transportation. The method comprises the steps of preprocessing the RFID data to realize identification of road network running vehicle tracks and obtain traffic parameters such as travel time, road section travel speed, road section flow and road network OD (Origin-Destination) through calculation; according to traffic parameter history data obtained through calculation, performing clustering analysis to traffic states, determining road situation discrimination thresholds and then discriminating the states according to real-time estimated traffic parameters. The urban road traffic parameter estimation and road situation discrimination method based on RFID data and the application system provided by the invention have the advantages that the traffic state discrimination accuracy is above 90 percent, the algorithm efficiency can meet the real-time demand of updating once per minute, the feasibility and the engineering applicability are better and a strong support can be provided for urban traffic state sensing.

Description

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Claims

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Application Information

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Owner TONGJI UNIV
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