JDR Vol.13 No.1 pp. 6-13
doi: 10.20965/jdr.2018.p0006


Estimation of Originating-Destination Trips in Yangon by Using Big Data Source

Thein Aye Zin*,†, Kyaing*, Ko Ko Lwin**, and Yoshihide Sekimoto**

*Yangon Technological University (YTU)
Insein Road, Gyogone, Insein 11011, Yangon, Myanmar

Corresponding author

**Institute of Industrial Science (IIS), University of Tokyo, Tokyo, Japan

September 1, 2017
February 1, 2018
February 20, 2018
big data, mobile phone data, the movement of people, trip estimation, Yangon

The ubiquitous massive mobile phone data generation presents new opportunities to determine the requirements of transportation, disaster management and public health care systems. Currently, data from mobile phone records can help in identifying the location of the users while they are making trips. Generally, this estimation is achieved using traditional data collection methods; however, these methods are difficult to apply in developing countries with rapidly growing cities owing to the high population and limitation in conducting a survey. Call detail records (CDRs) are used as base data because they are valuable data sources and can reduce the cost and time limitations. The aim of this study is to estimate origin-destination (OD) trips from each zone by using the CDRs. The OD trips are estimated by using the CDRs of one week taken from Myanmar Post and Telecommunication mobile operator for over 1.9 million users per day in Yangon, the economic center of Myanmar. The OD trips are estimated from CDRs based on the location of the base station in a limited time window and time frame. If the same mobile users is observed in two different the ones within the time limit, it is assumed that the mobile user is coming out from the first zone and the trips represents an originating trip. This trip would be the destination trip for zone where the mobile user enters. In this study, the originating (outgoing) and destination trips (incoming) from each township on a weekday and weekend are determined. These data are useful for infrastructure development and urban transportation planning.

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Last updated on Mar. 16, 2018