To promote inclusive, low-carbon mobility in African LIC cities, by piloting Big Data applications to generate data, benchmark performance, and draw policy insights.
This project will look at the following questions and themes.
Policy Levers: What are the main levers for mode share and what is the role of data? What cities have achieved high or low transit ridership, cycling, etc., and what factors / policies explain their differences?
Big Data Technology: What are the opportunities and risks of big data applications in HVT cities?
Informal (Paratransit): What is role of informal transport in the global South and how to enable transition towards a clean, affordable & efficient solution for HVT?
Increased mobility data collection in African LIC cities, where little mobility data has historically been available (due to cost of traditional data collection methods), to guide and support planning which promotes inclusive, low-carbon mobility.
Data collection technologies will include a mix of User Movement Analytics integrated mobile apps, USSD/WhatsApp/Web based surveys, and limited field surveys.
The Mobility Observatory and associated data collection techniques will be deployed in six African cities, and then proceed to develop Mobility Action Plans in two of these cities.
This research will create actionable mobility plans in two research cities, and inspire greater uptake of the mobility observatory platform across African LIC cities, and deployment of the data collection techniques to be developed and tested through the course of this research, which make use of existing affordable technologies.
This research is aimed at African government agencies, transport authorities and research organisations.
Globally, as a result of COVID-19, travel patterns have been in a constant state of flux. It is hypothesized that trends developing during this period may continue beyond the pandemic.
Through the collection of mobility data at scale, and affordably, objective measurement of mobility indicators could enable greater understanding of the nature of people’s changed travel behaviour, and the corresponding impact on mobility networks.