A real-time deployable model predictive control-based cooperative platooning approach for connected and autonomous vehicles
Recently, model predictive control (MPC)-based platooning strategies have been developed
for connected and autonomous vehicles (CAVs) to enhance traffic performance by enabling …
for connected and autonomous vehicles (CAVs) to enhance traffic performance by enabling …
A cooperative driving strategy for merging at on-ramps based on dynamic programming
Cooperative driving emerges as a promising way to improve efficiency and safety for
Connected and Automated Vehicles (CAVs). Its key idea is to design a strategy to schedule …
Connected and Automated Vehicles (CAVs). Its key idea is to design a strategy to schedule …
Plexe: A platooning extension for Veins
Cooperative driving in general and Cooperative Adaptive Cruise Control (CACC) or
platooning in particular require blending control theory, communications and networking, as …
platooning in particular require blending control theory, communications and networking, as …
Computing systems for autonomous driving: State of the art and challenges
The recent proliferation of computing technologies (eg, sensors, computer vision, machine
learning, and hardware acceleration) and the broad deployment of communication …
learning, and hardware acceleration) and the broad deployment of communication …
Platoon based cooperative driving model with consideration of realistic inter-vehicle communication
Recent developments of information and communication technologies (ICT) have enabled
vehicles to timely communicate with each other through wireless technologies, which will …
vehicles to timely communicate with each other through wireless technologies, which will …
Model-based deep reinforcement learning for CACC in mixed-autonomy vehicle platoon
This paper proposes a model-based deep reinforcement learning (DRL) algorithm for
cooperative adaptive cruise control (CACC) of connected vehicles. Differing from most …
cooperative adaptive cruise control (CACC) of connected vehicles. Differing from most …
Dolphins: Dataset for collaborative perception enabled harmonious and interconnected self-driving
Abstract Vehicle-to-Everything (V2X) network has enabled collaborative perception in
autonomous driving, which is a promising solution to the fundamental defect of stand-alone …
autonomous driving, which is a promising solution to the fundamental defect of stand-alone …
A selective federated reinforcement learning strategy for autonomous driving
Currently, the complex traffic environment challenges the fast and accurate response of a
connected autonomous vehicle (CAV). More importantly, it is difficult for different CAVs to …
connected autonomous vehicle (CAV). More importantly, it is difficult for different CAVs to …
A review on cooperative adaptive cruise control (CACC) systems: Architectures, controls, and applications
Connected and automated vehicles (CAVs) have the potential to address the safety, mobility
and sustainability issues of our current transportation systems. Cooperative adaptive cruise …
and sustainability issues of our current transportation systems. Cooperative adaptive cruise …
DQ-GAT: Towards safe and efficient autonomous driving with deep Q-learning and graph attention networks
Autonomous driving in multi-agent dynamic traffic scenarios is challenging: the behaviors of
road users are uncertain and are hard to model explicitly, and the ego-vehicle should apply …
road users are uncertain and are hard to model explicitly, and the ego-vehicle should apply …