Toward trustworthy decision-making for autonomous vehicles: A robust reinforcement learning approach with safety guarantees
While autonomous vehicles are vital components of intelligent transportation systems,
ensuring the trustworthiness of decision-making remains a substantial challenge in realizing …
ensuring the trustworthiness of decision-making remains a substantial challenge in realizing …
Human Knowledge Enhanced Reinforcement Learning for Mandatory Lane-Change of Autonomous Vehicles in Congested Traffic
Y Huang, Y Gu, K Yuan, S Yang, T Liu… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Mandatory lane-change scenarios are often challenging for autonomous vehicles in
complex environments. In this paper, a human-knowledge-enhanced reinforcement learning …
complex environments. In this paper, a human-knowledge-enhanced reinforcement learning …
Personalized Decision-Making and Control for Automated Vehicles Based on Generative Adversarial Imitation Learning
Automated driving is one of the main trends in automotive field. However, existing algorithms
for automated driving are mostly designed based on statistical rules without considering the …
for automated driving are mostly designed based on statistical rules without considering the …
Human feedback enhanced autonomous intelligent systems: a perspective from intelligent driving
Artificial intelligence empowers the rapid development of autonomous intelligent systems
(AISs), but it still struggles to cope with open, complex, dynamic, and uncertain …
(AISs), but it still struggles to cope with open, complex, dynamic, and uncertain …
NeuroFlow: Development of lightweight and efficient model integration scheduling strategy for autonomous driving system
E Seo, G Shin, E Lee - arXiv preprint arXiv:2312.09588, 2023 - arxiv.org
This paper proposes a specialized autonomous driving system that takes into account the
unique constraints and characteristics of automotive systems, aiming for innovative …
unique constraints and characteristics of automotive systems, aiming for innovative …
Continual Reinforcement Learning for Autonomous Driving with Application on Velocity Control under Various Environment
D Wei, J Xing, S Yang, Y Lu… - 2023 7th CAA …, 2023 - ieeexplore.ieee.org
Reinforcement learning based methods are extensively studied in autonomous driving.
However, most existing methods, suffering from catastrophic forgetting, only work properly …
However, most existing methods, suffering from catastrophic forgetting, only work properly …