Research advances and challenges of autonomous and connected ground vehicles
Autonomous vehicle (AV) technology can provide a safe and convenient transportation
solution for the public, but the complex and various environments in the real world make it …
solution for the public, but the complex and various environments in the real world make it …
Partially observable markov decision processes in robotics: A survey
Noisy sensing, imperfect control, and environment changes are defining characteristics of
many real-world robot tasks. The partially observable Markov decision process (POMDP) …
many real-world robot tasks. The partially observable Markov decision process (POMDP) …
The ind dataset: A drone dataset of naturalistic road user trajectories at german intersections
Automated vehicles rely heavily on data-driven methods, especially for complex urban
environments. Large datasets of real world measurement data in the form of road user …
environments. Large datasets of real world measurement data in the form of road user …
A journey towards fully autonomous driving-fueled by a smart communication system
Autonomous driving solutions stretch over different disciplines and technologies eg,
sensors, communication, computation, machine learning, data analytic, etc., that need to be …
sensors, communication, computation, machine learning, data analytic, etc., that need to be …
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 …
Automated driving in uncertain environments: Planning with interaction and uncertain maneuver prediction
Automated driving requires decision making in dynamic and uncertain environments. The
uncertainty from the prediction originates from the noisy sensor data and from the fact that …
uncertainty from the prediction originates from the noisy sensor data and from the fact that …
Decision making for autonomous driving considering interaction and uncertain prediction of surrounding vehicles
Autonomous driving requires decision making in dynamic and uncertain environments. The
uncertainty from the prediction originates from the noisy sensor data and from the fact that …
uncertainty from the prediction originates from the noisy sensor data and from the fact that …
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 …
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 …
Reinforcement learning for autonomous driving with latent state inference and spatial-temporal relationships
Deep reinforcement learning (DRL) provides a promising way for learning navigation in
complex autonomous driving scenarios. However, identifying the subtle cues that can …
complex autonomous driving scenarios. However, identifying the subtle cues that can …