Cooperation-aware reinforcement learning for merging in dense traffic
Decision making in dense traffic can be challenging for autonomous vehicles. An
autonomous system only relying on predefined road priorities and considering other drivers …
autonomous system only relying on predefined road priorities and considering other drivers …
Reinforcement learning with iterative reasoning for merging in dense traffic
Maneuvering in dense traffic is a challenging task for autonomous vehicles because it
requires reasoning about the stochastic behaviors of many other participants. In addition, the …
requires reasoning about the stochastic behaviors of many other participants. In addition, the …
Interactive decision making for autonomous vehicles in dense traffic
D Isele - 2019 IEEE Intelligent Transportation Systems …, 2019 - ieeexplore.ieee.org
Dense urban traffic environments can produce situations where accurate prediction and
dynamic models are insufficient for successful autonomous vehicle motion planning. We …
dynamic models are insufficient for successful autonomous vehicle motion planning. We …
Merging in congested freeway traffic using multipolicy decision making and passive actor-critic learning
Merging in congested freeway traffic is a significant challenge toward realizing fully
automated (level 4) driving. Merging vehicles need to decide not only how to merge safely …
automated (level 4) driving. Merging vehicles need to decide not only how to merge safely …
Interaction-aware decision making with adaptive strategies under merging scenarios
In order to drive safely and efficiently under merging scenarios, autonomous vehicles should
be aware of their surroundings and make decisions by interacting with other road …
be aware of their surroundings and make decisions by interacting with other road …
Deep multi-agent reinforcement learning for highway on-ramp merging in mixed traffic
On-ramp merging is a challenging task for autonomous vehicles (AVs), especially in mixed
traffic where AVs coexist with human-driven vehicles (HDVs). In this paper, we formulate the …
traffic where AVs coexist with human-driven vehicles (HDVs). In this paper, we formulate the …
Novel decision-making strategy for connected and autonomous vehicles in highway on-ramp merging
Z el abidine Kherroubi, S Aknine… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
High-speed highway on-ramp merging is a significant challenge toward realizing fully
automated driving (level 4). Connected Autonomous Vehicles (CAVs), that combine …
automated driving (level 4). Connected Autonomous Vehicles (CAVs), that combine …
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 …
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 …
Multi-agent reinforcement learning for cooperative lane changing of connected and autonomous vehicles in mixed traffic
Autonomous driving has attracted significant research interests in the past two decades as it
offers many potential benefits, including releasing drivers from exhausting driving and …
offers many potential benefits, including releasing drivers from exhausting driving and …