Physical-Social Nexus

A major driver of progress in smart cities is the ever-increasing interconnectivity between everyday physical devices such as mobile devices, household appliances, and vehicles, coupled with the rise in sensor instrumentation in city infrastructure (e.g. roads and buildings). 

This interconnectivity culminates in social-physical networks, which are revolutionizing a variety of industries that shape cities and the interactions that take place, from transportation to health care, to water, to energy. 

The goals of this cluster are threefold. First, to investigate the impacts of information and technology on human networks in terms of opinion formation and behavior, i.e. how technological disruptions in the physical network impact social networks. Second, to study how our growing understanding of human activity can be leveraged to manage physical networks better. Third, to further explore the social-physical nexus, that is, how humans-as-sensors coupled with information from physical networks affect the overall urban systems.


A Tale of Three Cities: Harnessing Techno-social Networks for Spatial Equity

Led by Surabhi Sharma

This project aims to study the global trend of proliferation of smart devices and how their connectivity has had a radical impact on how we consume and share information. This project focuses on media networks constituted by the multiplication of technologies that promise access and equity, but which often exacerbate spatial and information inequities that may interact and compound. In particular, the project compares three Indian Ocean cities: Abu Dhabi, Mumbai, and Singapore.

Electric Vehicle Carsharing and Traffic Flow Dynamics

Led by Saif Eddin Jabari

This project aims to develop new codes and tests to maximise the use and efficiency of charsharing systems with a particular focus on the city of Abu Dhabi. Electric vehicle (EV) market penetration is projected to increase at an exponential rate and is expected to dominate vehicle fleets in the coming 20-30 years. Carsharing services have been shown to be effective in reducing the number of cars on the road. However, EV carsharing is a risky investment that adds operational constraints that can make a system unsustainable in some cities. The underlying problem is that one-way carsharing systems, like other Mobility-on-Demand (MOD) systems, require some degree of rebalancing to be effective in meeting demand, depending on the service area covered and demand patterns. Through this research, carsharing service providers will gain access to new rebalancing code and test results that measure effectiveness with non-EV and EV systems, thereby reducing operating costs for EV carsharing and other EV-based MOD systems.

Stealthy Attacks on Autonomous Vehicle-based Control Systems and Their Defenses

Led by Muhammad Shafique

This research conducted in collaboration with the Center for Cyber Security aims to investigate attacks and defenses for the machine learning modules in connected automated vehicles (CAV). With increased automation comes increased vulnerability to cyber-attacks that can hack a vehicle’s electronic systems. Researchers have demonstrated an ability to take over a vehicle’s electronic systems and cause crashes. The research focuses on a new type of attacks on the deep neural networks of CAV, the so-called Backdoored Neural Networks, that only behave maliciously when triggered by specific inputs and on the relevant mitigation strategies.