  Second-order macroscopic continuum models have been constantly improving for
decades to reproduce the empirical observations. Recently, a series of
experimental studies have suggested that the stochastic factors contribute
significantly to destabilizing traffic flow. Nevertheless, the traffic flow
stability of the stochastic second-order macroscopic continuum model hasn't
received the attention it deserves in past studies. More importantly, we have
found that the destabilizing aspect of stochasticity is still not correctly
validated in the existing theoretical stability analysis. In this paper, we
analytically study the impact of stochasticity on traffic flow stability for a
general stochastic second-order macroscopic model by using the direct Lyapunov
method. Numerical simulations have been carried out for different typical
stochastic second-order macroscopic models. Our analytical stability analysis
has been validated, and our methodology has been proved more efficient. Our
study has theoretically revealed that the presence of stochasticity has a
destabilizing effect in stochastic macroscopic models.
