  This work presents an integrated framework of: vehicle dynamics models, with
a particular attention to instabilities and traffic waves; vehicle energy
models, with particular attention to accurate energy values for strongly
unsteady driving profiles; and sparse Lagrangian controls via automated
vehicles, with a focus on controls that can be executed via existing technology
such as adaptive cruise control systems. This framework serves as a key
building block in developing control strategies for human-in-the-loop traffic
flow smoothing on real highways. In this contribution, we outline the
fundamental merits of integrating vehicle dynamics and energy modeling into a
single framework, and we demonstrate the energy impact of sparse flow smoothing
controllers via simulation results.
