Situational awareness is crucial for developing sustainable urban planning frameworks for the future. Saudi Arabia’s growing population of 28 million is expected to double by 2032. Riyadh is currently undergoing a radical transformation by introducing a new urban transportation system with the Riyadh Metro and bus networks, the global public urban transportation project. The rapidly growing population demand in Riyadh and the unique cultural and social tapestry of the Kingdom of Saudi Arabia introduce another dimension to the complexity of urban transportation.
Our goal in this project was to develop tools to understand the mobility patterns of the city’s inhabitants to ensure that its services and infrastructures are growing in pace to meet the growing demands of this burgeoning population. This involved extracting reliable mobility data on urban trips and their frequency from passive data, coupled with existing buses and taxi demand to support the transit system’s adoption and operation in Riyadh. We developed algorithms to combine semantically enriched GIS data on infrastructure and economic activity distribution to extract human daily trip chains (urban activity) and identify potential transit demand and frequency.