Abstract
A Digital Twin is a digital replica of a living or non-living physical
entity, and this emerging technology has attracted extensive attention
from different industries during the past decade. Although a few Digital
Twin studies have been conducted in the transportation domain very
recently, there is no systematic research with a holistic framework
connecting various mobility entities together. In this study, by
leveraging both connected vehicle technology and cloud computing, an
Mobility Digital Twin (MDT) framework is developed, which consists of
three building blocks in the physical space (namely Human, Vehicle, and
Traffic), and their associated Digital Twins in the digital space. The
cloud architecture is built with Amazon Web Services (AWS) to
accommodate the proposed MDT framework and to implement its digital
functionalities of storage, modeling, learning, simulation, and
prediction. The effectiveness of the MDT framework is shown through the
case studies of three digital building blocks with their key
microservices: the Human Digital Twin with user management and driver
type classification, the Vehicle Digital Twin with cloud-based Advanced
Driver-Assistance Systems (ADAS), and the Traffic Digital Twin with
traffic flow monitoring and variable speed limit.