Blockchain intelligence for internet of vehicles: Challenges and solutions
With the development of communication and networking technologies, the Internet of
Vehicles (IoV) has become the foundation of smart transportation. The development of …
Vehicles (IoV) has become the foundation of smart transportation. The development of …
[HTML][HTML] Regional route guidance with realistic compliance patterns: Application of deep reinforcement learning and MPC
Solving link-based route guidance problems for large-scale networks is computationally
challenging and faces practical issues, such as spatial–temporal data coverage. Thus …
challenging and faces practical issues, such as spatial–temporal data coverage. Thus …
An overview of reinforcement learning-based approaches for smart home energy management systems with energy storages
The paper's state-of-the-art review focuses on an in-depth evaluation of smart home energy
management systems which employ reinforcement learning-based methods to integrate …
management systems which employ reinforcement learning-based methods to integrate …
Blockchain-based secure and trusted data sharing scheme for autonomous vehicle underlying 5G
This paper proposes a blockchain-based secure and reliable data sharing scheme for
autonomous vehicles (AVs). It aims to secure data sharing among AVs. We integrate the fifth …
autonomous vehicles (AVs). It aims to secure data sharing among AVs. We integrate the fifth …
AI-empowered trajectory anomaly detection and classification in 6G-V2X
G Raja, M Begum, S Gurumoorthy… - IEEE Transactions …, 2022 - ieeexplore.ieee.org
The immense growth of Autonomous Vehicles (AVs) and networking technologies have
paved the way for advanced Intelligent Transportation Systems (ITS). AVs increase data …
paved the way for advanced Intelligent Transportation Systems (ITS). AVs increase data …
Hierarchical decision-making framework for multiple UCAVs autonomous confrontation
Y Hou, X Liang, J Zhang, M Lv… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Autonomous decision-making for air confrontation between unmanned combat aerial
vehicles remains hard to be designed due to dynamic situations and complex interactions …
vehicles remains hard to be designed due to dynamic situations and complex interactions …
A hybrid driving decision-making system integrating markov logic networks and connectionist AI
Connectionist artificial intelligence (AI) can power many critical tasks for connected and
autonomous vehicles (CAVs). However, connectionist AI lacks interpretability and usually …
autonomous vehicles (CAVs). However, connectionist AI lacks interpretability and usually …
Self-organized routing for autonomous vehicles via deep reinforcement learning
Routing for autonomous vehicles with global traffic information and sufficient direct
cooperation among vehicles has been widely studied to relieve traffic congestion in recent …
cooperation among vehicles has been widely studied to relieve traffic congestion in recent …
Longitudinal control of automated vehicles: A novel approach by integrating deep reinforcement learning with intelligent driver model
Deep reinforcement learning (DRL) provides a promising approach for the implementation
of autonomous driving. By utilizing a trained DRL model as the longitudinal controller, the …
of autonomous driving. By utilizing a trained DRL model as the longitudinal controller, the …
Recent advances in reinforcement learning-based autonomous driving behavior planning: A survey
Autonomous driving (AD) holds the potential to revolutionize transportation efficiency, but its
success hinges on robust behavior planning (BP) mechanisms. Reinforcement learning (RL) …
success hinges on robust behavior planning (BP) mechanisms. Reinforcement learning (RL) …