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Identification of Trip Characteristics in Urban Rail Transit System Using WIFI Information

Southern African Transport Conference. Identification of Trip Characteristics in Urban Rail Transit System Using WIFI Information. Sirui Nan Chang'an University Email: 447661975@qq.com Tel:(+86)17782569437. CONTANTS. 01. 02. Detection. Introduction. 03. 04. Conclusion. Case study.

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Identification of Trip Characteristics in Urban Rail Transit System Using WIFI Information

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  1. Southern AfricanTransport Conference Identification of Trip Characteristics in Urban Rail Transit System Using WIFI Information Sirui Nan Chang'an University Email: 447661975@qq.com Tel:(+86)17782569437

  2. CONTANTS 01 02 Detection Introduction 03 04 Conclusion Case study

  3. 1.Introduction • Intelligent transportation system place more emphasis on using the existing infrastructure more efficiently • Travel characteristics of passengers are the basis of passenger induction, emergency management and ticketing • Modern traffic technology can accurately acquire passengers' location, time and other tags WIFI : high speed, low cost, high precision and high sampling rate GPS cannot be obtained in the underground space The sampling rate of bluetooth is about 1-3% The cell phone contains the privacy information WIFI DEVICE

  4. 2. Detection Data transmission process of detection devices The collected data of detection equipment will upload to the central data platform every 30 seconds. Second step First step The device can obtain the MAC address information Layout the testing equipment with different stations Third step Fourth step The central data platform analyzes the information identified by each WiFi device Each device transmits the acquired information to the central data platform

  5. 3. Case study On October 15, 2016 Do experiment Xi’an Metro Line 1 and line 2 At Sa jin qiao ,An yuan men Zhong lou , Wu lu kou station Verified by AFC data.

  6. 4. Case study • The maximum / minimum travel time between stations • Assuming that the transfer time follows a lognormal distribution, and the confidence level is 95%，using SPSS to perform the Kolmogorov-Smirnov test

  7. 4. Case study Parameters of Kolmogorov-Smirnov test

  8. 4. Conclusion WiFi information detection equipment can collect unique MAC address and identify travel characteristics. In the future, the data can be used to further improve the accuracy of passengers' travel characteristics recognition, and obtain more travel characteristics information.

  9. With great thanks to: Southern Africa-China Transportation Cooperation Center Sirui Nan Chang'an University Email: 447661975@qq.com Tel:(+86)17782569437

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