Autonomous vehicular overtaking maneuver: A survey and taxonomy
Autonomous vehicles (AVs) are the next-generation driver-less vehicular entities with
advanced technologies. Overtaking is an important and challenging maneuver that needs to …
advanced technologies. Overtaking is an important and challenging maneuver that needs to …
Convolutional neural network-based lane-change strategy via motion image representation for automated and connected vehicles
The lane-change decision-making module of automated and connected vehicles (ACVs) is
one of the most crucial and challenging issues to be addressed. Motivated by human beings' …
one of the most crucial and challenging issues to be addressed. Motivated by human beings' …
Trustworthy autonomous driving via defense-aware robust reinforcement learning against worst-case observational perturbations
Despite the substantial advancements in reinforcement learning (RL) in recent years,
ensuring trustworthiness remains a formidable challenge when applying this technology to …
ensuring trustworthiness remains a formidable challenge when applying this technology to …
Explaining a deep reinforcement learning (DRL)-based automated driving agent in highway simulations
As deep learning models have become increasingly complex, it is critical to understand their
decision-making, particularly in safety-relevant applications. In order to support a …
decision-making, particularly in safety-relevant applications. In order to support a …
An empirical study of ddpg and ppo-based reinforcement learning algorithms for autonomous driving
S Siboo, A Bhattacharyya, RN Raj, SH Ashwin - IEEE Access, 2023 - ieeexplore.ieee.org
Autonomous vehicles mitigate road accidents and provide safe transportation with a smooth
traffic flow. They are expected to greatly improve the quality of the elderly or people with …
traffic flow. They are expected to greatly improve the quality of the elderly or people with …
Effect of number of lanes on traffic characteristics of reinforcement learning based autonomous driving
Traffic characteristics such as signalized intersections and high vehicle density combined
with low vehicle speeds account for 12-55% increase in commute time. Increasing the …
with low vehicle speeds account for 12-55% increase in commute time. Increasing the …
High‐level decision‐making for autonomous overtaking: An MPC‐based switching control approach
XF Wang, WH Chen, J Jiang… - IET Intelligent Transport …, 2024 - Wiley Online Library
The key motivation of this paper lies in the development of a high‐level decision‐making
framework for autonomous overtaking maneuvers on two‐lane country roads with dynamic …
framework for autonomous overtaking maneuvers on two‐lane country roads with dynamic …
Blockchain-FRL for Vehicular Lane-Changing: Towards Traffic, Data and Training Safety
Reinforcement learning has been adopted to improve the efficiency of vehicular lane
changing (LC) decisions. However, since the local vehicular data needs to be uploaded to …
changing (LC) decisions. However, since the local vehicular data needs to be uploaded to …
Game-Theoretic Decision-Making Method and Motion Planning for Autonomous Vehicles in Overtaking
L Cai, H Guan, QH Xu, X Jia… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Overtaking is a common driving behaviour used by human drivers while driving. Therefore,
the decision on overtaking is very important in the automatic driving decision. To be able to …
the decision on overtaking is very important in the automatic driving decision. To be able to …
Holistic Deep-Reinforcement-Learning-based Training of Autonomous Navigation Systems
In recent years, Deep Reinforcement Learning emerged as a promising approach for
autonomous navigation of ground vehicles and has been utilized in various areas of …
autonomous navigation of ground vehicles and has been utilized in various areas of …