  While bringing convenience to people, the growing number of vehicles on road
already cause inevitable traffic congestion. Some traffic congestion happen
with observable reasons, but others occur without apparent reasons or
bottlenecks, which referred to as phantom jams, are caused by traditional
vehicle following model. In order to alleviate the traffic instability caused
by phantom jam, several models have been proposed with the development of
intelligent transportation system (ITS). these have been proved to be able to
suppress traffic instability in the ideal situation. But in road scenarios,
uncertainties of vehicle state measurements and time delay caused by on-board
sensors, inter-vehicle communications and control system of vehicles will
affect the performance of the existing models severely, and cannot be ignored.
In this paper, a novel predictable bilateral control model-PBCM, which consists
of best estimation and state prediction is proposed to determine accurate
acceleration values of the host vehicle in traffic flow to alleviate traffic
instability. Theoretical analysis and simulation results show that our model
could reduce the influence of the measurement errors and the delay caused by
communication and control system effectively, control the state of the vehicles
in traffic flow accurately, thus achieve the goal of restrain the instability
of traffic flow.
