  Our current transportation system suffers from a number of problems in terms
of safety, mobility, and environmental sustainability. The emergence of
innovative intelligent transportation systems (ITS) technologies, and in
particular connected and automated vehicles (CAVs), provides many opportunities
to address the aforementioned issues. In this paper, we propose a hierarchical
ramp merging system that not only generates microscopic cooperative maneuvers
for CAVs on the ramp to merge into the mainline traffic flow, but also provides
controllability of the ramp inflow rate, thereby enabling macroscopic traffic
flow control. A centralized optimal control-based approach is proposed to
smooth the merging flow, improve the system-wide mobility, and decrease the
overall fuel consumption of the network. Linear quadratic trackers in both
finite horizon and receding horizon forms are developed to solve the
optimization problem in terms of path planning and sequence determination,
where a microscopic vehicle fuel consumption model is applied. Extensive
traffic simulation runs have been conducted using PTV VISSIM to evaluate the
impact of the proposed system on a segment of SR-91 E in Corona, California.
The results confirm that under the regulated inflow rate, the proposed system
can avoid potential traffic congestion and improve mobility (e.g., VMT/VHT) up
to 147%, with a 47% fuel savings compared to the conventional ramp metering and
the ramp without any control approach.
