Cities have depended on each other since the origins of civilization. The original trade networks evolved to networks of cities that enabled the flow of knowledge embedded in physical resources and people.
Today, with the advent of AI, robots, and sensors, networks within and between cities increasingly rely on intelligent machines. This, in turn, has promoted a plethora of new connections between urban system components. Thus, to ensure sustainable urban development across different layers, it is imperative to understand the interactions between the physical, social, and digital networks.
The goals of this cluster are threefold. First, to use multiple perspectives in order to better understand the connections between different components of the urban systems. Second, to explore how such connections also affect the interactions across cities leading to different developmental stages, different challenges, and potentially different solutions. Third, to leverage the interactions between the different types of networks to propose innovative yet tangible solutions to global challenges.
Improving Multimodal Mobility in Urban Networks
Traffic congestion is a challenge across cities worldwide, with multiple transport modes competing for limited road space. At the same time, new technologies are triggering rapid changes in mobility. This project aims to develop novel modeling and optimization tools for designing, operating and controlling advanced mobility systems, especially during a transition period where conventional and automated vehicles coexist. The idea is to build solutions that improve the performance of the overall system while taking into account the interactions and trade-offs across the different modes.