Formation control for a fleet of autonomous ground vehicles: A survey
Autonomous/unmanned driving is the major state-of-the-art step that has a potential to
fundamentally transform the mobility of individuals and goods. At present, most of the …
fundamentally transform the mobility of individuals and goods. At present, most of the …
Interpretable end-to-end urban autonomous driving with latent deep reinforcement learning
Unlike popular modularized framework, end-to-end autonomous driving seeks to solve the
perception, decision and control problems in an integrated way, which can be more …
perception, decision and control problems in an integrated way, which can be more …
Interaction-aware trajectory prediction and planning for autonomous vehicles in forced merge scenarios
Merging is, in general, a challenging task for both human drivers and autonomous vehicles,
especially in dense traffic, because the merging vehicle typically needs to interact with other …
especially in dense traffic, because the merging vehicle typically needs to interact with other …
A belief state planner for interactive merge maneuvers in congested traffic
Autonomous driving in urban environments requires the capability of merging into narrow
gaps. In cases of high traffic density this becomes more complex since one must consider …
gaps. In cases of high traffic density this becomes more complex since one must consider …
Learning highway ramp merging via reinforcement learning with temporally-extended actions
Several key scenarios, such as intersection navigation, lane changing, and ramp merging,
are active areas of research in autonomous driving. In order to properly navigate these …
are active areas of research in autonomous driving. In order to properly navigate these …
Automatically generated curriculum based reinforcement learning for autonomous vehicles in urban environment
We address the problem of learning autonomous driving behaviors in urban intersections
using deep reinforcement learning (DRL). DRL has become a popular choice for creating …
using deep reinforcement learning (DRL). DRL has become a popular choice for creating …
Probabilistic prediction from planning perspective: Problem formulation, representation simplification and evaluation metric
Accurate probabilistic prediction for intention and motion of road users is a key prerequisite
to achieve safe and high-quality decision-making and motion planning for autonomous …
to achieve safe and high-quality decision-making and motion planning for autonomous …
Risk-based merging decisions for autonomous vehicles
W Jin, M Islam, M Chowdhury - Journal of safety research, 2022 - Elsevier
Introduction: The safe freeway merging operation for fully Autonomous Vehicles (AVs) in
mixed traffic (ie, the presence of AVs and non-AVs in a traffic stream) is a challenging task …
mixed traffic (ie, the presence of AVs and non-AVs in a traffic stream) is a challenging task …
Autonomous navigation in interaction-based environments—A case of non-signalized roundabouts
M Rodrigues, A McGordon, G Gest… - IEEE Transactions on …, 2018 - ieeexplore.ieee.org
To reduce the number of collision fatalities at crossroads intersections, many countries have
started replacing intersections with non-signalized roundabouts, forcing the drivers to be …
started replacing intersections with non-signalized roundabouts, forcing the drivers to be …
Highway on-ramp merging for mixed traffic: Recent advances and future trends
SA Fernandez, MAM Marinho… - 2021 IEEE 29th …, 2021 - ieeexplore.ieee.org
Due to the ability to support a wide range of applications and to involve infrastructure
elements, connected and automated vehicles (CAVs) technology has played an important …
elements, connected and automated vehicles (CAVs) technology has played an important …