Efficient intersection planning is one of the most challenging tasks for an autonomous
vehicle at present. Politeness to other traffic participants and reaction to surrounding …

Autonomous vehicles (AVs) need to interact with other traffic participants who can be either
cooperative or aggressive, attentive or inattentive. Such different characteristics can lead to …

In this work we put forward a predictive trajectory planning framework to help autonomous
vehicles plan future trajectories. We develop a partially observable Markov decision process …

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 …

Driving through dense urban environments is difficult for autonomous vehicles because they
must reason about the unknown intentions of a large number of road users while also …

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

Decision-making and planning are the core aspects of autonomous driving systems. These
factors are crucial for improving the safety, driving experience, and travel efficiency of …

In this article, we present an efficient planning system for automated vehicles in highly
interactive environments (EPSILON). EPSILON is an efficient interaction-aware planning …

For autonomous vehicles, scene understanding is still one of the major challenges, which
needs to be well handled to avoid jittery decisions and unsmooth trajectories. Furthermore …

Uncertainties in dynamical driving environments are crucial to the decision making and
trajectory planning modules for autonomous vehicles. Without proper handling of such …