On the Traffic Impacts of Optimally Controlled Connected and Automated Vehicles

Zhao, Liuhui; Malikopoulos, Andreas A.; Rios Torres, Jackeline

doi:10.1109/CCTA.2019.8920630

On the Traffic Impacts of Optimally Controlled Connected and Automated Vehicles

Conference · Thu Aug 01 04:00:00 EDT 2019

DOI:https://doi.org/10.1109/CCTA.2019.8920630· OSTI ID:1630520

Zhao, Liuhui ^[1]; Malikopoulos, Andreas A. ^[1]; ^[2]

University of Delaware
ORNL

The implementation of connected and automated vehicle (CAV) technologies enables a novel computational framework for real-time control actions aimed at optimizing energy consumption and associated benefits. Several research efforts reported in the literature to date have proposed decentralized control algorithms to coordinate CAVs in various traffic scenarios, e.g., highway on-ramps, intersections, and roundabouts. However, the impact of optimally coordinating CAVs on the performance of a transportation network has not been thoroughly analyzed yet. In this paper, we apply a decentralized optimal control framework in a transportation network and compare its performance to a baseline scenario consisting of human-driven vehicles. We show that introducing of CAVs yields radically improved roadway capacity and network performance.

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Research Organization:: Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)

Sponsoring Organization:: USDOE; USDOE Office of Energy Efficiency and Renewable Energy (EERE)

DOE Contract Number:: AC05-00OR22725

OSTI ID:: 1630520

Country of Publication:: United States

Language:: English

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