Inferring origin-destination flows using mobile phone data: A case study of Senegal

• Main Authors: Merkebe Getachew Demissie, Francisco Antunes, Carlos Bento, Santi Phithakkitnukoon, Titipat Sukhvibul
• Format: Conference Proceeding
• Published: 2018
• Subjects: Computer Science; Engineering
• Online Access: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84988892076&origin=inward; http://cmuir.cmu.ac.th/jspui/handle/6653943832/55511
• Institution: Chiang Mai University

© 2016 IEEE. In transportation planning, estimating the movement of people between a set of origins and destinations is a challenging task. This has been inferred in two way: from data on household socioeconomic attributes in each study zone or based on the characteristics of the study zones such as population, employment, number of cars, etc. However, developing these models can be difficult, especially in the developing countries where transport planners have limited budget to collect detailed transportation data. In this study, we use mobile phone data to estimate the origin-destination (OD) flows between districts of Senegal. We have developed two approaches to estimate commuting trips, recurring travel between one's place of residence and place of work, and irregular trips, which are not recurring, but found to be predominant in developing countries. The inferred OD flows from sample users are expanded using the total population from census data. The results demonstrate how mobile phone data can be used to sense movement of large portion of population more regularly and with reduced cost, especially, in circumstances where relevant data are unavailable or in poor supply.