The Kingdom’s Vision 2030 has focused on the continuous development of this crucial sector to promote the country’s status in this field. This will be accomplished by establishing a vision to develop internal transportation networks and planning, and to utilize the Kingdom’s distinguished location and status among other countries in the world, providing a unique logistics platform capable of becoming the main world trade center. The rapid economic and population growth of many cities in the modern age is posing new challenges. Concerns about future development and planning arise from the lack of a full understanding of the current state as well as how to plan for future states. To tackle these concerns, situational awareness is an important stance 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 which are currently the largest public urban transportation project in the world. The rapidly growing population demand in Riyadh, and the unique cultural and social tapestry of the Kingdom of Saudi Arabia, introduces another dimension to the complexity in urban transportation. The challenges stem from the need to understand the social and mobility patterns of the country’s inhabitants with specificity and to ensure the city’s services and infrastructures are growing at a pace to meet the growing demands of this burgeoning population. Our objectives involve extracting reliable urban trips and their frequency from passive data, coupled with existing demographics and taxi demand, to evaluate how the upcoming public transit systems will impact how residents use our transportation infrastructure and services. We use our derived understanding of human mobility activities and travel times to develop a coupled network approach for optimizing the interconnections of vehicle trips, and to improve traffic as an optimized flow of multiplex networks.