This CPS project is driven by largescale online multimodal transit feeds to achieve equilibrium in demand and supply relationship in transportation CPS systems through cyber-control.

Cyber-Physical Systems (CPS) are being increasingly deployed in critical infrastructures such as electric-power, water, transportation, and other networks. These deployments are facilitating real-time monitoring and closed-loop control by exploiting the advances in wireless sensor-actuator networks, the internet of “everything,” data-driven analytics, and machine-to-machine interfaces. CPS operations depend on the synergy of computational and physical components.

The cities in the U.S. and elsewhere in the developed world are experiencing a transformation: Many people demand denser neighborhood with mixed use, while they choose to utilize public transportation, rather than private cars, for their commute and other daily transportation needs. To support this trend, cities are in need of novel transportation and logistics services that can help address the needs of their citizens, boost their productivity, and increase the wellness of their lives. There are a number of emerging technologies that can address this challenge.

Autonomy-enabled transportation networks are rapidly becoming a prominent Cyber-Physical-Systems (CPS) application area with tremendous potential for societal impact, as the autonomous systems technology penetrates into aerial/road vehicles and as the concept of connected vehicles emerge. The potential opportunities are not gone unnoticed. For example, unmanned aerial vehicle (UAV) based delivery networks has already attracted innovative companies like Amazon, Google, and Matternet.

Parking can take up a significant amount of the trip costs (time and money) in urban travel. As such, it can considerably influence travelers' choices of modes, locations, and time of travel. The advent of smart sensors, wireless communications, social media and big data analytics offers a unique opportunity to tap parking's influence on travel to make the transportation system more efficient, cleaner, and more resilient. A cyber-physical social system for parking is proposed to realize parking's potential in achieving the above goals.

This project advances the scientific knowledge on design methods for improving the resilience of civil infrastructures to disruptions. To improve resilience, critical services in civil infrastructure sectors must utilize new diagnostic tools and control algorithms that ensure survivability in the presence of both security attacks and random faults, and also include the models of incentives of human decision makers in the design process.

The purpose of this research is to develop optimization and control techniques and integrate them with real-time simulation models to achieve load balancing in complex networks.  Our application case is the regional freight system.  Freight moves on rail and road networks which are also shared by passengers.  These networks today work independently, even though they are highly interdependent, and the result is inefficiencies in the form of congestion, pollution, and excess fuel consumption.

One of the challenges for the future cyber-physical systems is the exploration of large design spaces.  Evolutionary algorithms (EAs), which embody a simplified computational model of the mutation and selection mechanisms of natural evolution, are known to be effective for design optimization.  However, the traditional formulations are limited to choosing values for a predetermined set of parameters within a given fixed architecture.  This project explores techniques, based on the idea of hidden genes, which enable EAs to select a variable number of components, thereby expand