Urban intersections represent a complex environment for autonomous vehicles with many
sources of uncertainty. The vehicle must plan in a stochastic environment with potentially …

As automated vehicles begin operating on complex urban roads, precise decision making
for automated driving has been increasingly important for safe automated driving. In …

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 …

As autonomous vehicles begin venturing on the urban road, rational decision making is
essential for driving safety and efficiency. This paper presents a situation-aware decision …

This work examines the hypothesis that partially observable Markov decision process
(POMDP) planning with human driver internal states can significantly improve both safety …

Autonomous vehicles need to perform social accepted behaviors in complex urban
scenarios including human‐driven vehicles with uncertain intentions. This leads to many …

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 …

Driving autonomous vehicles safely through a complex urban environment remains a
difficult task. The sensor limitations, as well as the various occlusions in the urban …

In recent years, automated driving has gained the public spotlight as more prototypes are
tested amongst human drivers. Since driving is a social behavior, automated vehicles (AVs) …

Autonomous driving in urban areas requires avoiding other road users with only partial
observability of the environment. Observations are only partial because obstacles can …