  Routing controllability of connected and autonomous vehicles (CAVs) has been
shown to reduce the adverse effects of selfish routing on the network
efficiency. However, the assumption that CAV owners would readily allow
themselves to be controlled externally by a central agency for the good of the
system is unrealistic. In this paper, we propose a joint routing and pricing
control scheme that aims to incentivize CAVs to seek centrally controlled
system-optimal (SO) routing by saving on tolls while user equilibrium (UE)
seeking human-driven vehicles (HVs) are subject to a congestion charge. The
problem is formulated as a bi-level optimization program where the upper level
optimizes the dynamic toll rates using the network fundamental diagram (NFD)
and the lower level is a mixed equilibrium simulation-based dynamic traffic
assignment model (SBDTA) considering different combinations of SO-seeking CAVs.
We apply a feedback-based controller to solve for the optimal spatially
differentiated distance-based congestion charge from which SO-seeking CAVs are
exempt; but UE-seeking HVs are subject to the charge for entering the city
center. To capture the distinct microscopic behavior of CAVs in the mixed
autonomy traffic, we also implement an adaptive link fundamental diagram (FD)
within the SBDTA model. The proposed joint control scheme encourages CAV owners
to seek SO routing resulting in less total system travel time. It also
discourages UE-seeking HVs from congesting the city center. We demonstrate the
performance of the proposed scheme in both a small network and a large-scale
network of Melbourne, Australia.
