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 …

On-ramp merging is often associated with highly dynamic interactions between ego and
other vehicles, which are more challenging in dense traffic. Considering both the overall …

How to make precise multi-agent trajectory prediction is a crucial problem in the context of
autonomous driving. It is significant to have the ability to predict surrounding road …

High-speed highway on-ramp merging is a significant challenge toward realizing fully
automated driving (level 4). Connected Autonomous Vehicles (CAVs), that combine …

This article presents a data-driven framework for trajectory recommendation in automated
and cooperative driving. The considered cooperative driving maneuver is lane-merge …

Various cooperative merging control strategies at on-ramp have been proposed in the last
decade. Approximated vehicle longitudinal motion models, eg, kinematics model, have been …

When driving in urban environments, an autonomous vehicle must account for the
interaction with other traffic participants. It must reason about their future behavior, how its …

Despite the success of AI-enabled onboard perception, on-ramp merging has been one of
the main challenges for autonomous driving. Due to limited sensing range of onboard …

Achieving the highest levels of automated driving will require effective solutions to the key
challenging maneuver of highway on-ramp merging. This paper extends our previous work …

On the highway, human drivers continuously make decisions adapting their driving
behavior. In some of these, for example near highway ramp-entrances, they adjust intuitively …