Current advances in the development of autonomous cars suggest that driverless cars may
see wide-scale deployment in the near future. Research by both industry and academia is …

We propose a new scheme to learn motion planning constraints from human driving
trajectories. Behavioral and motion planning are the key components in an autonomous …

Trajectory planning has generally been framed as finding the lowest cost one from a set of
trajectory candidates, where the cost function has been hand-crafted with carefully tuned …

The prospect of driverless cars wide-scale deployment is imminent owing to the advances in
robotics, computational power, communications, and sensor technologies. This promises …

The convergence of mechanical, electrical, and advanced ICT technologies, driven by
artificial intelligence and 5G vehicle-to-everything (5G-V2X) connectivity, will help to develop …

Speed planning is one of the tasks that a self-driving vehicle carries out. A complete planner
should consider and balance passengers comfort, trip time and energy consumption. This …

Trajectory planning is one of the most important modules of the Autonomous Driving
Systems (ADSs), which aims to achieve a safe and comfortable interaction between the …

This thesis is concerned with the development of trajectory planning approaches targeting
autonomous driving applications in dynamic environments shared with other traffic …

Autonomous vehicles have the potential to drastically improve the safety, efficiency and cost
of transportation. Instead of a driver, an autonomous vehicle is controlled by an algorithm …

Quantifying and encoding occupants' preferences as an objective function for the tactical
decision making of autonomous vehicles is a challenging task. This paper presents a low …