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 …
Strategic decisions: survey, taxonomy, and future directions from artificial intelligence perspective
Strategic Decision-Making is always challenging because it is inherently uncertain,
ambiguous, risky, and complex. By contrast to tactical and operational decisions, strategic …
ambiguous, risky, and complex. By contrast to tactical and operational decisions, strategic …
A survey on autonomous vehicle control in the era of mixed-autonomy: From physics-based to AI-guided driving policy learning
This paper serves as an introduction and overview of the potentially useful models and
methodologies from artificial intelligence (AI) into the field of transportation engineering for …
methodologies from artificial intelligence (AI) into the field of transportation engineering for …
Navigating occluded intersections with autonomous vehicles using deep reinforcement learning
Providing an efficient strategy to navigate safely through unsignaled intersections is a
difficult task that requires determining the intent of other drivers. We explore the …
difficult task that requires determining the intent of other drivers. We explore the …
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 …
Decision-making framework for autonomous driving at road intersections: Safeguarding against collision, overly conservative behavior, and violation vehicles
S Noh - IEEE Transactions on Industrial Electronics, 2018 - ieeexplore.ieee.org
In this paper, we propose a decision-making framework for autonomous driving at road
intersections that determines appropriate maneuvers for an autonomous vehicle to navigate …
intersections that determines appropriate maneuvers for an autonomous vehicle to navigate …
Game-theoretic modeling of traffic in unsignalized intersection network for autonomous vehicle control verification and validation
For a foreseeable future, autonomous vehicles (AVs) will operate in traffic together with
human-driven vehicles. Their planning and control systems need extensive testing …
human-driven vehicles. Their planning and control systems need extensive testing …
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 …
due to the uncertainty in the behaviors of surrounding vehicles and the different types of …
Safe reinforcement learning with scene decomposition for navigating complex urban environments
Navigating urban environments represents a complex task for automated vehicles. They
must reach their goal safely and efficiently while considering a multitude of traffic …
must reach their goal safely and efficiently while considering a multitude of traffic …
Reinforcement learning with probabilistic guarantees for autonomous driving
Designing reliable decision strategies for autonomous urban driving is challenging.
Reinforcement learning (RL) has been used to automatically derive suitable behavior in …
Reinforcement learning (RL) has been used to automatically derive suitable behavior in …