Autonomous and semiautonomous intersection management: A survey

Z Zhong, M Nejad, EE Lee - IEEE Intelligent Transportation …, 2020 - ieeexplore.ieee.org
Intersections are a major source of traffic delays and accidents within modern transportation
systems. Compared to signalized intersection management, autonomous intersection …

Predictive energy-efficient driving strategy design of connected electric vehicle among multiple signalized intersections

H Dong, W Zhuang, B Chen, Y Lu, S Liu, L Xu… - … Research Part C …, 2022 - Elsevier
Signalized intersections dominate traffic flow in urban areas, resulting in increased energy
consumption and travel delay for the vehicles involved. To mitigate the negative effect of …

An AI-Assisted Systematic Literature Review of the Impact of Vehicle Automation on Energy Consumption

M Noroozi, HR Moghaddam, A Shah… - IEEE Transactions …, 2023 - ieeexplore.ieee.org
Impacts of vehicle automation and connectivity have been studied widely from the
perspectives of fuel economy, ecology, and safety. Synthesis of various segments of this …

Optimal control of connected and automated vehicles at multiple adjacent intersections

B Chalaki, AA Malikopoulos - IEEE Transactions on Control …, 2021 - ieeexplore.ieee.org
In this article, we establish a decentralized optimal control framework for connected and
automated vehicles (CAVs) crossing multiple adjacent, multilane signal-free intersections to …

A cellular automata traffic flow model combined with a BP neural network based microscopic lane changing decision model

M Liu, J Shi - Journal of Intelligent Transportation Systems, 2019 - Taylor & Francis
The purpose of this study is to propose a cellular automata (CA) traffic flow model with high
accuracy for lane change decision and name it LCCAM. A driving simulator experiment was …

Conflict-free cooperation method for connected and automated vehicles at unsignalized intersections: Graph-based modeling and optimality analysis

C Chen, Q Xu, M Cai, J Wang… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Connected and automated vehicles have shown great potential in improving traffic mobility
and reducing emissions, especially at unsignalized intersections. Previous research has …

A research and educational robotic testbed for real-time control of emerging mobility systems: From theory to scaled experiments [applications of control]

B Chalaki, LE Beaver, AMI Mahbub… - IEEE Control …, 2022 - ieeexplore.ieee.org
Emerging mobility systems, for example, connected and automated vehicles (CAVs), shared
mobility, and electric vehicles, mark a paradigm shift in which myriad opportunities exist for …

Online longitudinal trajectory planning for connected and autonomous vehicles in mixed traffic flow with deep reinforcement learning approach

Y Cheng, X Hu, K Chen, X Yu, Y Luo - Journal of Intelligent …, 2023 - Taylor & Francis
This manuscript presents an Adam optimization-based Deep Reinforcement Learning model
for Mixed Traffic Flow control (ADRL-MTF), so as to guide Connected and Autonomous …

Connected automated vehicle trajectory optimization along signalized arterial: A decentralized approach under mixed traffic environment

Q Wang, Y Gong, X Yang - Transportation research part C: emerging …, 2022 - Elsevier
Trajectory optimization, as a key connected automated vehicles (CAVs) operation task, has
the potential to mitigate traffic congestion, lower energy consumption, and increase the …

A hybrid planning approach based on MPC and parametric curves for overtaking maneuvers

R Lattarulo, J Pérez Rastelli - Sensors, 2021 - mdpi.com
Automated Driving Systems (ADS) have received a considerable amount of attention in the
last few decades, as part of the Intelligent Transportation Systems (ITS) field. However, this …