Planning and decision-making for connected autonomous vehicles at road intersections: A review

S Li, K Shu, C Chen, D Cao - Chinese Journal of Mechanical Engineering, 2021‏ - Springer
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 …

[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 …

A survey of deep RL and IL for autonomous driving policy learning

Z Zhu, H Zhao - IEEE Transactions on Intelligent Transportation …, 2021‏ - ieeexplore.ieee.org
Autonomous driving (AD) agents generate driving policies based on online perception
results, which are obtained at multiple levels of abstraction, eg, behavior planning, motion …

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 sha** humanity's
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

X He, B Lou, H Yang, C Lv - IEEE Transactions on Intelligent …, 2022‏ - ieeexplore.ieee.org
Reinforcement learning has demonstrated its potential in a series of challenging domains.
However, many real-world decision making tasks involve unpredictable environmental …

Toward personalized decision making for autonomous vehicles: a constrained multi-objective reinforcement learning technique

X He, C Lv - Transportation research part C: emerging technologies, 2023‏ - Elsevier
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 …

Trustworthy autonomous driving via defense-aware robust reinforcement learning against worst-case observational perturbations

X He, W Huang, C Lv - Transportation Research Part C: Emerging …, 2024‏ - Elsevier
Despite the substantial advancements in reinforcement learning (RL) in recent years,
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

R Bautista-Montesano, R Galluzzi, K Ruan, Y Fu… - … research part C …, 2022‏ - Elsevier
This paper develops an integrated safety-enhanced reinforcement learning (RL) and model
predictive control (MPC) framework for autonomous vehicles (AVs) to navigate unsignalized …

[HTML][HTML] Reinforcement learning-based autonomous driving at intersections in carla simulator

R Gutiérrez-Moreno, R Barea, E López-Guillén… - Sensors, 2022‏ - mdpi.com
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 …

[HTML][HTML] Graph reinforcement learning-based decision-making technology for connected and autonomous vehicles: Framework, review, and future trends

Q Liu, X Li, Y Tang, X Gao, F Yang, Z Li - Sensors, 2023‏ - mdpi.com
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 …