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Planning and decision-making for connected autonomous vehicles at road intersections: A review
Planning and decision-making technology at intersections is a comprehensive research
problem in intelligent transportation systems due to the uncertainties caused by a variety of …
problem in intelligent transportation systems due to the uncertainties caused by a variety of …
[كتاب][B] Algorithms for decision making
MJ Kochenderfer, TA Wheeler, KH Wray - 2022 - books.google.com
A broad introduction to algorithms for decision making under uncertainty, introducing the
underlying mathematical problem formulations and the algorithms for solving them …
underlying mathematical problem formulations and the algorithms for solving them …
A survey of deep RL and IL for autonomous driving policy learning
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 …
Uncertainties in onboard algorithms for autonomous vehicles: Challenges, mitigation, and perspectives
Autonomous driving is considered one of the revolutionary technologies sha** 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 …
Robust decision making for autonomous vehicles at highway on-ramps: A constrained adversarial reinforcement learning approach
Reinforcement learning has demonstrated its potential in a series of challenging domains.
However, many real-world decision making tasks involve unpredictable environmental …
However, many real-world decision making tasks involve unpredictable environmental …
Toward personalized decision making for autonomous vehicles: a constrained multi-objective reinforcement learning technique
Reinforcement learning promises to provide a state-of-the-art solution to the decision
making problem of autonomous driving. Nonetheless, numerous real-world decision making …
making problem of autonomous driving. Nonetheless, numerous real-world decision making …
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 …
Autonomous navigation at unsignalized intersections: A coupled reinforcement learning and model predictive control approach
This paper develops an integrated safety-enhanced reinforcement learning (RL) and model
predictive control (MPC) framework for autonomous vehicles (AVs) to navigate unsignalized …
predictive control (MPC) framework for autonomous vehicles (AVs) to navigate unsignalized …
[HTML][HTML] Reinforcement learning-based autonomous driving at intersections in carla simulator
Intersections are considered one of the most complex scenarios in a self-driving framework
due to the uncertainty in the behaviors of surrounding vehicles and the different types of …
due to the uncertainty in the behaviors of surrounding vehicles and the different types of …
[HTML][HTML] Graph reinforcement learning-based decision-making technology for connected and autonomous vehicles: Framework, review, and future trends
The proper functioning of connected and autonomous vehicles (CAVs) is crucial for the
safety and efficiency of future intelligent transport systems. Meanwhile, transitioning to fully …
safety and efficiency of future intelligent transport systems. Meanwhile, transitioning to fully …