Planning a safe and comfortable trajectory in complex traffic scenarios is very challenging
because there are many constraints to consider, such as vehicle dynamics constraints and …

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

Trajectory planning is key component for autonomous vehicles. However, most existing
trajectory planning methods which utilized a set of fixed weights to evaluate an optimal …

We present a framework for robust autonomous driving motion planning system in urban
environments which includes trajectory refinement, trajectory interpolation, avoidance of …

Current sensing and control of self-driving vehicles based on full-view recognition is hard to
keep a high-frequency with a fast moving vehicle, as increasingly complex computation is …

Automated driving in urban settings is challenging. Human participant behavior is difficult to
model, and conventional, rule-based Automated Driving Systems (ADSs) tend to fail when …

In this paper, we present a hierarchical framework for decision-making and planning on
highway driving tasks. We utilized intelligent driving models (IDM and MOBIL) to generate …

Curvy roads are a particular type of urban road scenario, wherein the curvature of the road
centerline changes drastically. This paper is focused on the trajectory planning task for …

In behavior planning for autonomous vehicles, other traffic participants have to be
considered. This is typically achieved by using a prediction model to estimate their future …

This article advances state-of-the-art automated driving systems with a comprehensive
framework that encompasses decision making, maneuver planning, and trajectory tracking …