1. Southern African Transport Conference
Identification of Trip Characteristics in Urban Rail Transit System Using
WIFI Information
Sirui Nan
Chang'an University
Tel:(+86)

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

3. 1. Introduction Intelligent transportation system
WIFI : high speed, low cost, high precision and high sampling rate
The sampling rate of bluetooth is about 1-3%
GPS cannot be obtained in the underground space
The cell phone contains the privacy information
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 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.
First step
Second step
Layout the testing equipment
with different stations
The device can obtain
the MAC address information
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
Wu-Sa
Wu-An
Wu-Zhong
Sa-An
Sa-Zhong
An-Zhong
Maximum travel time/min
9.5
20.41
20.11
19.81
7.25
Minimum travel time/min
3.9
6.8
6.2
5.7
4.01
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 Test interval
Wu-An
Wu-Zhong
Sa-An
Sa-Zhong
sample size N
14323
17526
11390
16391
Normal distribution parameter
mean
standard deviation
Maximum difference
absolute value
.262
.251
.255
.258
Kolmogorov-Smirnov Z
7.767
6.990
7.223
7.419
Bilateral progressive significance
.774
.730
.755
.772

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: Sirui Nan Chang'an University
Southern Africa-China
Transportation
Cooperation Center
Sirui Nan
Chang'an University
Tel:(+86)