AI-based fog and edge computing: A systematic review, taxonomy and future directions
Resource management in computing is a very challenging problem that involves making
sequential decisions. Resource limitations, resource heterogeneity, dynamic and diverse …
sequential decisions. Resource limitations, resource heterogeneity, dynamic and diverse …
[HTML][HTML] A comprehensive survey on the application of deep and reinforcement learning approaches in autonomous driving
Abstract Recent advances in Intelligent Transport Systems (ITS) and Artificial Intelligence
(AI) have stimulated and paved the way toward the widespread introduction of Autonomous …
(AI) have stimulated and paved the way toward the widespread introduction of Autonomous …
A survey on federated learning: The journey from centralized to distributed on-site learning and beyond
S AbdulRahman, H Tout… - IEEE Internet of …, 2020 - ieeexplore.ieee.org
Driven by privacy concerns and the visions of deep learning, the last four years have
witnessed a paradigm shift in the applicability mechanism of machine learning (ML). An …
witnessed a paradigm shift in the applicability mechanism of machine learning (ML). An …
A systematic survey of control techniques and applications in connected and automated vehicles
Vehicle control is one of the most critical challenges in autonomous vehicles (AVs) and
connected and automated vehicles (CAVs), and it is paramount in vehicle safety, passenger …
connected and automated vehicles (CAVs), and it is paramount in vehicle safety, passenger …
Suppression of mainbeam deceptive jammer with FDA-MIMO radar
Suppression of radar-to-radar jammers, especially the mainbeam jammers, has been an
urgent demand in vehicular sensing systems with the expected increased number of …
urgent demand in vehicular sensing systems with the expected increased number of …
Artificial intelligence applications in the development of autonomous vehicles: A survey
The advancement of artificial intelligence (AI) has truly stimulated the development and
deployment of autonomous vehicles (AVs) in the transportation industry. Fueled by big data …
deployment of autonomous vehicles (AVs) in the transportation industry. Fueled by big data …
Robust lane detection from continuous driving scenes using deep neural networks
Lane detection in driving scenes is an important module for autonomous vehicles and
advanced driver assistance systems. In recent years, many sophisticated lane detection …
advanced driver assistance systems. In recent years, many sophisticated lane detection …
Perspectives on the impact of machine learning, deep learning, and artificial intelligence on materials, processes, and structures engineering
The fields of machining learning and artificial intelligence are rapidly expanding, impacting
nearly every technological aspect of society. Many thousands of published manuscripts …
nearly every technological aspect of society. Many thousands of published manuscripts …
Human-like decision making for autonomous driving: A noncooperative game theoretic approach
Considering that human-driven vehicles and autonomous vehicles (AVs) will coexist on
roads in the future for a long time, how to merge AVs into human drivers' traffic ecology and …
roads in the future for a long time, how to merge AVs into human drivers' traffic ecology and …
A survey of deep RL and IL for autonomous driving policy learning
Z Zhu, H Zhao - IEEE Transactions on Intelligent Transportation …, 2021 - ieeexplore.ieee.org
Autonomous driving (AD) agents generate driving policies based on online perception
results, which are obtained at multiple levels of abstraction, eg, behavior planning, motion …
results, which are obtained at multiple levels of abstraction, eg, behavior planning, motion …