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Our current transportation system suffers from a number of problems in termsof safety, mobility, and environmental sustainability. The emergence ofinnovative intelligent transportation systems (ITS) technologies, and inparticular connected and automated vehicles (CAVs), provides many opportunitiesto address the aforementioned issues. In this paper, we propose a hierarchicalramp merging system that not only generates microscopic cooperative maneuversfor CAVs on the ramp to merge into the mainline traffic flow, but also providescontrollability of the ramp inflow rate, thereby enabling macroscopic trafficflow control. A centralized optimal control-based approach is proposed tosmooth the merging flow, improve the system-wide mobility, and decrease theoverall fuel consumption of the network. Linear quadratic trackers in bothfinite horizon and receding horizon forms are developed to solve theoptimization problem in terms of path planning and sequence determination,where a microscopic vehicle fuel consumption model is applied. Extensivetraffic simulation runs have been conducted using PTV VISSIM to evaluate theimpact 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 systemcan avoid potential traffic congestion and improve mobility (e.g., VMT/VHT) upto 147%, with a 47% fuel savings compared to the conventional ramp metering andthe ramp without any control approach.

Optimal Control-Based Eco-Ramp Merging System for Connected and Automated Electric Vehicles