Autonomous driving security: State of the art and challenges
The autonomous driving industry has mushroomed over the past decade. Although
autonomous driving has undoubtedly become one of the most promising technologies of this …
autonomous driving has undoubtedly become one of the most promising technologies of this …
Uncertainties in onboard algorithms for autonomous vehicles: Challenges, mitigation, and perspectives
K Yang, X Tang, J Li, H Wang, G Zhong… - IEEE Transactions …, 2023 - ieeexplore.ieee.org
Autonomous driving is considered one of the revolutionary technologies shaping humanity's
future mobility and quality of life. However, safety remains a critical hurdle in the way of …
future mobility and quality of life. However, safety remains a critical hurdle in the way of …
Towards socially responsive autonomous vehicles: A reinforcement learning framework with driving priors and coordination awareness
The advent of autonomous vehicles (AVs) alongside human-driven vehicles (HVs) has
ushered in an era of mixed traffic flow, presenting a significant challenge: the intricate …
ushered in an era of mixed traffic flow, presenting a significant challenge: the intricate …
Autonomous highway driving using deep reinforcement learning
The operational space of an autonomous vehicle (AV) can be diverse and vary significantly.
Due to this, formulating a rule based decision maker for selecting driving maneuvers may …
Due to this, formulating a rule based decision maker for selecting driving maneuvers may …
Risk-informed decision-making and control strategies for autonomous vehicles in emergency situations
This paper proposes risk-informed decision-making and control methods for autonomous
vehicles (AVs) under severe driving conditions, where many vehicle interactions occur on …
vehicles (AVs) under severe driving conditions, where many vehicle interactions occur on …
Game-theoretic modeling of multi-vehicle interactions at uncontrolled intersections
Motivated by the need for simulation tools for testing, verification and validation of
autonomous driving systems that operate in traffic consisting of both autonomous and …
autonomous driving systems that operate in traffic consisting of both autonomous and …
Combining reinforcement learning with rule-based controllers for transparent and general decision-making in autonomous driving
The design of high-level decision-making systems is a topical problem in the field of
autonomous driving. In this paper, we combine traditional rule-based strategies and …
autonomous driving. In this paper, we combine traditional rule-based strategies and …
A MPC combined decision making and trajectory planning for autonomous vehicle collision avoidance
M Ammour, R Orjuela, M Basset - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Increasing focus is being paid to ensuring safety in autonomous driving. The current paper
addresses the challenge of collision avoidance with dynamic surrounding vehicles in …
addresses the challenge of collision avoidance with dynamic surrounding vehicles in …
Mtd-gpt: A multi-task decision-making gpt model for autonomous driving at unsignalized intersections
Autonomous driving technology is poised to transform transportation systems. However,
achieving safe and accurate multi-task decision-making in complex scenarios, such as …
achieving safe and accurate multi-task decision-making in complex scenarios, such as …
Transferable and adaptable driving behavior prediction
While autonomous vehicles still struggle to solve challenging situations during on-road
driving, humans have long mastered the essence of driving with efficient, transferable, and …
driving, humans have long mastered the essence of driving with efficient, transferable, and …