A rise in population, along with urbanization, has been causing an increase in demand for urban transportation services in the sub-Saharan Africa countries. In these countries, mobility of people is mainly ensured by bus services and a large-scale informal public transport service, which is known as paratransit (e.g., car rapides in Senegal, Tro Tros in Ghana, taxis in Uganda and Ethiopia, and Matatus in Kenya). Transport demand estimation is a challenging task, particularly in developing countries, mainly due to its expensive and time-consuming data collection requirements. Without accurate demand estimation, it is difficult for transport operators to provide their services and make other important decisions. In this paper, we present a methodology to estimate passenger demand for public transport services using cell phone data. Significant origins and destinations of inhabitants are extracted and used to build origin-destination matrices that resemble travel demand. Based on the inferred travel demand, we are able to reasonably suggest strategic locations for public transport services such as paratransit and taxi stands, as well as new transit routes. The outcome of this study can be useful for the development of policies that can potentially help fulfill the mobility needs of city inhabitants.

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.