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A Survey on the Coordination of Connected and Automated Vehicles at Intersections and Merging at Highway On-Ramps
TLDR
The developments and the research trends in coordination with the CAVs that have been reported in the literature to date are summarized and remaining challenges and potential future research directions are discussed.
Automated and Cooperative Vehicle Merging at Highway On-Ramps
TLDR
This paper addresses the problem of optimally coordinating CAVs at merging roadways to achieve smooth traffic flow without stop-and-go driving with an optimization framework and an analytical closed-form solution that allows online coordination of vehicles at merging zones.
Supervisory Power Management Control Algorithms for Hybrid Electric Vehicles: A Survey
TLDR
This paper surveys the control algorithms for hybrid electric vehicles (HEVs) and plug-in HEVs (PHEVs) that have been reported in the literature to date and includes a classification of the algorithms in terms of their implementation and the chronological order of their appearance.
Optimal control and coordination of connected and automated vehicles at urban traffic intersections
TLDR
A decentralized optimal control framework whose solution yields for each vehicle the optimal acceleration/deceleration at any time in the sense of minimizing fuel consumption is presented.
Online Optimal Control of Connected Vehicles for Efficient Traffic Flow at Merging Roads
TLDR
A framework and a closed-form solution that optimize the acceleration profile of each vehicle in terms of fuel economy while avoiding collision with other vehicles at the merging zone is presented.
Zero-Shot Autonomous Vehicle Policy Transfer: From Simulation to Real-World via Adversarial Learning
TLDR
A zero-shot transfer of an autonomous driving policy from simulation to University of Delaware’s scaled smart city with adversarial multi-agent reinforcement learning with the addition of adversarial training considerably improves the performance of the policies after transfer to the real world compared to Gaussian noise injection.
Optimal Control for Speed Harmonization of Automated Vehicles
TLDR
The proposed approach significantly reduces both fuel consumption and travel time and yields the optimal acceleration/deceleration of each vehicle under the hard safety constraint of rear-end collision avoidance.
Impact of Partial Penetrations of Connected and Automated Vehicles on Fuel Consumption and Traffic Flow
TLDR
It is shown that fuel consumption is adversely affected for medium and high traffic while benefits are realized for travel time under the same traffic conditions.
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