On-road trajectory planning is a critical module in an autonomous driving system. Instead of
using a path-velocity decomposition or longitudinal-lateral decomposition strategy, this work …

In order to achieve the safe and efficient navigation of mobile robots, it is essential to
consider both the environmental geometry and kinodynamic constraints of robots. We …

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

Efficient trajectory planning for intelligent vehicles in dynamic environments is a non-trivial
task due to the diversity and complexity of driving scenarios. It requires the planner to be …

Navigating through roadworks represents one of the main sources of safety risk for
Connected and Autonomous Vehicles (CAVs) due to the altered road layouts. The built-in …

Planning trajectories for automated vehicles in urban environments requires methods with
high generality, long planning horizons, and fast update rates. Using a path-velocity …

Safe and adaptable motion planning for autonomous vehicles remains an open problem in
urban environments, where the variability of situations and behaviors may become …

In this Ph. D. thesis, we study how autonomous vehicles can learn to act safely and avoid
accidents, despite sharing the road with human drivers whose behaviours are uncertain. To …

In the present studies of autonomous driving systems, motion planning of automated
vehicles in complex traffic scenarios is a tough issue. The problem of adjusting automated …

The acceptance of automated driving is under the potential threat of motion sickness. It
hinders the passengers' willingness to perform secondary activities. In order to mitigate …