  Digital twinning of vehicles is an iconic application of digital twins, as
the concept of twinning dates back to the twinning of NASA space vehicles.
Although digital twins (DTs) in the automotive industry have been recognized
for their ability to improve efficiency in design and manufacturing, their
potential to enhance land vehicle operation has yet to be fully explored. Most
existing DT research on vehicle operations, aside from the existing body of
work on autonomous guided vehicles (AGVs), focuses on electrified passenger
cars. However, the use and value of twinning varies depending on the goal,
whether it is to provide cost-efficient and sustainable freight transport
without disruptions, sustainable public transport focused on passenger
well-being, or fully autonomous vehicle operation. In this context, DTs are
used for a range of applications, from real-time battery health monitoring to
enabling fully autonomous vehicle operations. This leads to varying
requirements, complexities, and maturities of the implemented DT solutions.
This paper analyzes recent trends in DT-driven efficiency gains for freight,
public, and autonomous vehicles and discusses their required level of maturity
based on a maturity tool. The application of our DT maturity tool reveals that
most DTs have reached level 3 and enable real-time monitoring. Additionally,
DTs of level 5 already exist in closed environments, allowing for restricted
autonomous operation.
