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

M. Demissie, Francisco Antunes, C. Bento, S. Phithakkitnukoon, Titipat Sukhvibul
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引用次数: 22

Abstract

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.
利用移动电话数据推断始发目的地流量:以塞内加尔为例
在交通规划中,估计一组出发地和目的地之间的人员流动是一项具有挑战性的任务。这是通过两种方式推断出来的:从每个研究区域的家庭社会经济属性数据,或基于研究区域的特征,如人口、就业、汽车数量等。然而,开发这些模型可能很困难,特别是在发展中国家,交通规划者的预算有限,无法收集详细的交通数据。在这项研究中,我们使用移动电话数据来估计塞内加尔地区之间的始发目的地(OD)流量。我们开发了两种方法来估计通勤旅行,一种是经常往返于居住地和工作地点之间的旅行,另一种是不定期的旅行,这种旅行并不经常发生,但在发展中国家占主导地位。从样本用户推断的OD流量使用人口普查数据中的总人口进行扩展。研究结果表明,移动电话数据可以更有规律地用于感知大部分人口的移动,并降低成本,特别是在相关数据不可用或供应不足的情况下。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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