  Autonomous trucks are expected to fundamentally transform the freight
transportation industry, and the technology is advancing rapidly. According to
some of the major players, the Autonomous Transfer Hub Network (ATHN) business
model is the most likely future for the industry. ATHNs make use of transfer
hubs to hand off trailers between human-driven trucks and autonomous trucks.
Autonomous trucks then carry out the transportation between the hubs, while
conventional trucks serve the first and last mile. This paper presents a
Constraint Programming (CP) model to schedule the ATHN operations to perform a
given set of orders. The model is used to, for the first time, provide a
detailed quantitative study of the benefits of ATHNs by considering a real case
study where actual operations are modeled and optimized with high fidelity. It
is found that solving this large-scale optimization problem with CP is
computationally feasible, and that ATHNs may bring significant cost savings.
