This thesis investigates interaction-aware trajectory planning for highway merging
scenarios. It is an effort to make navigation of the highway merging scenario safer by …

A key problem to be solved for automated driving is to generate a feasible trajectory
regarding the constraints imposed by vehicle physical limits and road surface. This paper …

In this paper we present a novel approach to address the lane change maneuver for
Autonomous Vehicles (AVs). We frame this challenge as a parametric Model Predictive …

An optimal path tracking controller for autonomous vehicles is presented to coordinate
longitudinal and lateral vehicle dynamics. With the nonlinear model predictive controller …

Driving behavior prediction plays an increasingly important role in the development of
autonomous driving functions and Advanced Driver Assistance Systems (ADAS). The more …

Motion planners for autonomous driving improve traffic safety through collision-free motion
generation along the path. However, conventional motion planners render passengers …

This paper presents a framework to plan and execute autonomous parking maneuvers in
complex parking scenarios. We formulate a minimum-time optimal control problem for …

Autonomous driving technology can greatly increase road safety and reduce accidents, and
has become a hot research topic in academia and industry today. However, traditional …

Optimal trajectory planning of autonomous vehicles is a crucial yet difficult task, since the
dynamic constraints of vehicles are hard to consider, and the optimal trajectory is difficult to …

Motivated by the promising benefits of connected and autonomous vehicles (CAVs) in
improving fuel efficiency, mitigating congestion, and enhancing safety, numerous theoretical …