  In this paper we extend the Aw-Rascle-Zhang (ARZ) non-equilibrium traffic
flow model to take into account the look-ahead capability of connected and
autonomous vehicles (CAVs), and the mixed flow dynamics of human driven and
autonomous vehicles. The look-ahead effect of CAVs is captured by a non-local
averaged density within a certain distance (the look-ahead distance). We show,
using wave perturbation analysis, that increased look-ahead distance loosens
the stability criteria. Our numerical experiments, however, showed that a
longer look-ahead distance does not necessarily lead to faster convergence to
equilibrium states. We also examined the impact of spatial distributions and
market penetrations of CAVs and showed that increased market penetration helps
stabilizing mixed traffic while the spatial distribution of CAVs have less
effect on stability. The results revealed the potential of using CAVs to
stabilize traffic, and may provide qualitative insights on speed control in the
mixed autonomy environment.
