Riyadh is undergoing a radical transformation by building a new Metro system from scratch. It is currently the largest public urban transportation project in the world. This project modeled the flows and impact of the Metro on the wider city and look at operational strategies such as pricing, frequency, ridership rules. Methods to extract reliable urban trips and their frequency from passive data, coupled with existing buses and taxi demand to support the transit system adoption and operation in Riyadh.

We developed:

1)Algorithms to combine semantically enriched GIS data on land use, infrastructure, and economic activity distribution, to extract human daily trip chains (urban activities) and to identify potential transit demand and frequency.

2) Derived understanding of human activities, trip-chains and travel times for developing a coupled network approach to optimize the interconnections of vehicle trips car and buses.

We used the Coupled Networks approach: A small network 2 (metro) was coupled with the larger network 1 (road network). We explored various coupling mechanisms that resulted in the best performance in terms of travel times for existing conditions of OD demand and travel times. We also used a data integration approach, collecting data from existing bus and taxi trips using either crowd sourced cell phone applications or obtaining from existing taxi operators and other sources.