  Digital Twin, as an emerging technology related to Cyber-Physical Systems
(CPS) and Internet of Things (IoT), has attracted increasing attentions during
the past decade. Conceptually, a Digital Twin is a digital replica of a
physical entity in the real world, and this technology is leveraged in this
study to design a cooperative driving system at non-signalized intersections,
allowing connected vehicles to cooperate with each other to cross intersections
without any full stops. Within the proposed Digital Twin framework, we
developed an enhanced first-in-first-out (FIFO) slot reservation algorithm to
schedule the sequence of crossing vehicles, a consensus motion control
algorithm to calculate vehicles' referenced longitudinal motion, and a
model-based motion estimation algorithm to tackle communication delay and
packet loss. Additionally, an augmented reality (AR) human-machine-interface
(HMI) is designed to provide the guidance to drivers to cooperate with other
connected vehicles. Agent-based modeling and simulation of the proposed system
is conducted in Unity game engine based on a real-world map in San Francisco,
and the human-in-the-loop (HITL) simulation results prove the benefits of the
proposed algorithms with 20% reduction in travel time and 23.7% reduction in
energy consumption, respectively, when compared with traditional signalized
intersections.
