Enabling massive IoT toward 6G: A comprehensive survey
Nowadays, many disruptive Internet-of-Things (IoT) applications emerge, such as
augmented/virtual reality online games, autonomous driving, and smart everything, which …
augmented/virtual reality online games, autonomous driving, and smart everything, which …
Autonomous driving system: A comprehensive survey
J Zhao, W Zhao, B Deng, Z Wang, F Zhang… - Expert Systems with …, 2023 - Elsevier
Automation is increasingly at the forefront of transportation research, with the potential to
bring fully autonomous vehicles to our roads in the coming years. This comprehensive …
bring fully autonomous vehicles to our roads in the coming years. This comprehensive …
Deep reinforcement learning for autonomous driving: A survey
With the development of deep representation learning, the domain of reinforcement learning
(RL) has become a powerful learning framework now capable of learning complex policies …
(RL) has become a powerful learning framework now capable of learning complex policies …
Deep reinforcement learning for intelligent transportation systems: A survey
Latest technological improvements increased the quality of transportation. New data-driven
approaches bring out a new research direction for all control-based systems, eg, in …
approaches bring out a new research direction for all control-based systems, eg, in …
Adaptive digital twin and multiagent deep reinforcement learning for vehicular edge computing and networks
Technological advancements of urban informatics and vehicular intelligence have enabled
connected smart vehicles as pervasive edge computing platforms for a plethora of powerful …
connected smart vehicles as pervasive edge computing platforms for a plethora of powerful …
Survey of deep reinforcement learning for motion planning of autonomous vehicles
S Aradi - IEEE Transactions on Intelligent Transportation …, 2020 - ieeexplore.ieee.org
Academic research in the field of autonomous vehicles has reached high popularity in
recent years related to several topics as sensor technologies, V2X communications, safety …
recent years related to several topics as sensor technologies, V2X communications, safety …
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 …
A survey on intelligent control for multiagent systems
P Shi, B Yan - IEEE Transactions on Systems, Man, and …, 2020 - ieeexplore.ieee.org
In practice, the dual constraints of limited interaction capabilities and system uncertainties
make it difficult for large-scale multiagent systems (MASs) to achieve intelligent collaboration …
make it difficult for large-scale multiagent systems (MASs) to achieve intelligent collaboration …
Deep multi-agent reinforcement learning for highway on-ramp merging in mixed traffic
On-ramp merging is a challenging task for autonomous vehicles (AVs), especially in mixed
traffic where AVs coexist with human-driven vehicles (HDVs). In this paper, we formulate the …
traffic where AVs coexist with human-driven vehicles (HDVs). In this paper, we formulate the …