Autonomous vehicles are being developed to make road traffic safer in the future. The time
when autonomous vehicles are actually safe enough to be used in real traffic is a current …

Autonomous vehicles face numerous challenges to ensure safe operation in unpredictable
and hazardous conditions. The autonomous driving environment is characterized by high …

This thesis presents a novel framework for safe online trajectory planning of unmanned
vehicles through partially unknown environments. The basic planning problem is formulated …

Motion planning algorithms for urban automated driving must handle uncertainty due to
unknown intention and future motion of Dynamic Obstacles (DOs). Considering a single …

Trajectory planning is one of the most complex tasks that should be accomplished in order to
ensure vehicle autonomous driving. Trajectory planning can be classified into local and …

Ensuring the safety of autonomous vehicles (AV s) in uncertain traffic scenarios is a major
challenge. In this paper, we address the problem of computing the risk that AV s violate a …

Trajectory planning is a critical function in an autonomous vehicle, which is about generating
a local spatio-temporal curve with safety, traverse efficiency, and comfort factors considered …

Recently significant progress has been made in vehicle prediction and planning algorithms
for autonomous driving. However, it remains quite challenging for an autonomous vehicle to …

In 2017, the German ethics commission for automated and connected driving released 20
ethical guidelines for autonomous vehicles. It is now up to the research and industrial …

This study presents a general optimal trajectory planning (GOTP) framework for autonomous
vehicles (AVs) that can effectively avoid obstacles and guide AVs to complete driving tasks …