Olivier de Weck
Anas Faris Alfaris
Rapid economic and population growth occurring throughout Saudi Arabia are posing new opportunities and changes for the Kingdom. In particular, the concomitant growth in the Kingdom’s capital, Riyadh, is straining the city’s road network to the point of becoming a major hindrance to socioeconomic activity. Within the city, vehicular trips have increased at the rapid rate of 9% per annum since 1987, with trips on freeways expanding rapidly resulting in longer commuting time.
There is a great need to understand the intricacies inherent in the movement of people and flows of vehicles with respect to space and time. Understanding where people go--and when and why they do--is crucial to meeting the demands they place on the road network and other infrastructure. .
The Urban Traffic System (UTS) is a project that addresses the traffic system of Riyadh. Through it, we seek to gain a comprehensive understanding of the complexity, behavior and evolution of urban environments. UTS aims to have several perspectives on the urban transportation system of Riyadh, involving variables belonging to a range of layers impacting the traffic system on the macro and micro levels.
On the macro level, UTS attempts to understand the complexity of human mobility and its implications on the flows of vehicles around the road network of Riyadh. The human mobility model will take advantage of the high penetration rate of mobile phones in Saudi Arabia where it will utilize Call Detail Records (CDRs) to generate dynamic origin-destination (OD) matrices in addition to population estimates and land use based on users activities. Information about road network geometry together with several outputs from the model targeting the mobility of people around the city will be utilized within the vehicle flow model that will simulate the flows of vehicles on the road network around the day.
On the other hand, areas where flows demonstrate inefficiencies will be modeled and observed on a micro level for a deeper understanding of the interaction between demand and supply. The micro model will incorporate simulation-based optimization (SO) frameworks in order to identify new mobility strategies that account traditional metrics (e.g. travel time, throughput) as well as investigating more advanced metrics, such as network-wide energy consumption patterns, network-wide vehicle emissions and travel time reliability.