Mobility Digital Twin for Connected and Automated Vehicles

The Data Science Discipline of the School of ITEE is hosting the following guest seminar: 

Mobility Digital Twin for Connected and Automated Vehicles 

Speaker: Dr Ziran Wang (Purdue University) 
Host: Dr Yadan Luo

More Info: https://uq-ds-seminar.github.io/mobility-digital-twin/  

Abstract: Digital Twin is a digital replica of a living or nonliving physical entity, and this emerging technology attracted extensive attention from different industries during the past decade. In this talk, a Mobility Digital Twin (MDT) framework is introduced, which is defined as an Artificial Intelligence (AI)-based data-driven cloud-edge-device framework for mobility services. This MDT consists of three building blocks in the physical space (namely Human, Vehicle, and Traffic), and their associated Digital Twins in the digital space. An example cloud-edge architecture is built with Amazon Web Services (AWS) to accommodate the proposed MDT framework and to fulfill its digital functionalities of storage, modeling, learning, simulation, and prediction. The effectiveness of the MDT framework is presented by the case studies of multiple connected and automated vehicle (CAV) applications, benefiting our transportation systems regarding safety, efficiency, and environmental sustainability. 

Speaker Bio: Dr. Ziran Wang is currently an Assistant Professor in the Lyles School of Civil Engineering at Purdue University, where he directs the Purdue Digital Twin Lab. Previously, he worked as a Principal Researcher at Toyota Motor North America R&D in Silicon Valley, leading the Digital Twin roadmap at Toyota. Dr. Wang is serving as associate editor of IEEE Internet of Things Journal, IEEE Transactions on Intelligent Vehicles, and two other journals. He is also founding chair of IEEE Technical Committee on “Internet of Things in Intelligent Transportation Systems”. Dr. Wang is an author of 40+ peer-review publications and 50+ patent applications.