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Title:

Characterizing Travel Space-Time Trajectory on Urban Rail Transit Network Using Wi-Fi Data

Accession Number:

01590296

Record Type:

Component

Abstract:

Analyzing network travel trajectories, including route choices among lines and move traces within stations, is the foundation of passenger flow analysis for an urban rail transit (URT) system. Historically, our understanding of it remains limited because of a lack of detail data in both spatial and temporal dimensions. Recently, the WIFI service is available for URT passengers in more and more cities around the world. Transaction data obtained through the WIFI service system contain a large amount of archived information recording how passengers use the URT system. In order to characterize passengers travel space-time trajectories precisely, the authors propose a methodology using WIFI data. A super network, which combines route choices among lines and move traces within stations, is introduced to reconstruct the URT network and give a completed description of travel space-time trajectories. Using WIFI data from the URT system, an inference model, based on modified Received Signal Strength Indicator (RSSI) positioning algorithm, for passenger travel space-time trajectory is developed. Initial experiments have been conducted to test the reliability of the proposed methodology. The results show that it can accurately infer passengers’ comprehensive travel process both in network and stations, providing a basis for URT passenger flow analysis, fare clearing, routing guidance, operation organization, etc.

Supplemental Notes:

This paper was sponsored by TRB committee ABJ30 Standing Committee on Urban Transportation Data and Information Systems. Alternate title: Characterizing Travel Space-Time Trajectory on Urban Rail Transit Network Using WIFI Data

Monograph Accession #:

01584066

Report/Paper Numbers:

16-0132

Language:

English

Corporate Authors:

Transportation Research Board

500 Fifth Street, NW
Washington, DC 20001 United States

Authors:

Li, Sijie
Zhu, Wei
Guo, Le

Pagination:

14p

Publication Date:

2016

Conference:

Transportation Research Board 95th Annual Meeting

Location: Washington DC, United States
Date: 2016-1-10 to 2016-1-14
Sponsors: Transportation Research Board

Media Type:

Digital/other

Features:

Figures; References; Tables

Identifier Terms:

WiFi services

Uncontrolled Terms:

Space-time trajectories

Subject Areas:

Data and Information Technology; Public Transportation; I72: Traffic and Transport Planning

Source Data:

Transportation Research Board Annual Meeting 2016 Paper #16-0132

Files:

TRIS, TRB, ATRI

Created Date:

Jan 12 2016 4:18PM