A review of safe reinforcement learning: Methods, theory and applications
Reinforcement learning (RL) has achieved tremendous success in many complex decision
making tasks. When it comes to deploying RL in the real world, safety concerns are usually …
making tasks. When it comes to deploying RL in the real world, safety concerns are usually …
A comprehensive review on limitations of autonomous driving and its impact on accidents and collisions
A Chougule, V Chamola, A Sam… - IEEE Open Journal of …, 2023 - ieeexplore.ieee.org
The emergence of autonomous driving represents a pivotal milestone in the evolution of the
transportation system, integrating seamlessly into the daily lives of individuals due to its …
transportation system, integrating seamlessly into the daily lives of individuals due to its …
Fault-Tolerant cooperative driving at highway on-ramps considering communication failure
Cooperative driving has great potential to improve traffic safety and efficiency and has been
widely discussed in recent years. However, most existing researches only focus on the ideal …
widely discussed in recent years. However, most existing researches only focus on the ideal …
Deep reinforcement learning for autonomous vehicles: lane keep and overtaking scenarios with collision avoidance
SH Ashwin, R Naveen Raj - International Journal of Information …, 2023 - Springer
Numerous accidents and fatalities occur every year across the world as a result of the
reckless driving of drivers and the ever-increasing number of vehicles on the road. Due to …
reckless driving of drivers and the ever-increasing number of vehicles on the road. Due to …
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 …
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 …
Safe Reinforcement Learning for Automated Vehicles via Online Reachability Analysis
X Wang, M Althoff - IEEE Transactions on Intelligent Vehicles, 2023 - ieeexplore.ieee.org
Ensuring safe and capable motion planning is paramount for automated vehicles.
Traditional methods are limited in their ability to handle complex and unpredictable traffic …
Traditional methods are limited in their ability to handle complex and unpredictable traffic …
Safety in Traffic Management Systems: A Comprehensive Survey
Traffic management systems play a vital role in ensuring safe and efficient transportation on
roads. However, the use of advanced technologies in traffic management systems has …
roads. However, the use of advanced technologies in traffic management systems has …
Decision-making driven by driver intelligence and environment reasoning for high-level autonomous vehicles: a survey
Autonomous vehicle (AV) is expected to reshape the future transportation system, and its
decision-making is one of the most critical modules. Many current decision-making modules …
decision-making is one of the most critical modules. Many current decision-making modules …
Long-tail prediction uncertainty aware trajectory planning for self-driving vehicles
A typical trajectory planner of self-driving vehicles commonly relies on predicting the future
behavior of surrounding obstacles. Recently, deep learning technology has been widely …
behavior of surrounding obstacles. Recently, deep learning technology has been widely …