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.
The project’s 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 system will impact how residents use Riyadh’s transportation infrastructure and services.
In this project, we aim to develop algorithms to combine semantically enriched GIS data on infrastructure, and economic activity distribution, to extract human daily trip chains (urban activity) and to identify potential transit demand and frequency. Moreover, 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.
The Integrated Transit Systems (ITS) project aims to develop a framework to address the intricacies and coupling of socio and technical infrastructures. The project involves the use of a coupled network approach to connect the public transit system to an extensive road network, evaluate the transit system using travel times for existing demands, and to examine the effects of various coupling strategies.
In this project, we model the flows and impact of the Metro on Riyadh and investigate the operational strategies such as pricing, frequency and ridership patterns and constraints. This project will use a mixture of modeling and analysis methods such as complex networks modeling, machine learning and big data analytics to improve our understanding of the social and traffic dynamics of population demand and infrastructure supply in the fast-growing city of Riyadh. The project will utilize new ubiquitous technologies as a proxy to infer characteristics of the demand on infrastructures and conduct fine-grained analyses with temporal and spatial resolutions.
The research methodology for ITS involves the usage of data generated from social media and location-aware devices in combination with other datasets to infer mobility patterns in order to understand transportation and energy infrastructures pertaining to daily commuting. In the dynamic visualizations and interactive features of our system, we showcase the results of our analysis by providing an integrated approach that addresses the interdependence of social and mobility dynamics in urban and infrastructure development.