This paper presents a hierarchical motion planning approach based on discrete optimization
method. Well-coupled longitudinal and lateral planning strategies with adaptability features …

We present a motion planner for autonomous on-road driving, especially on highways. It
adapts the idea of a on-road state lattice. A focused search is performed in the previously …

This paper outlines a predictive maneuver-planning method for autonomous vehicle
navigating public highway traffic. The method integrates discrete maneuvering decisions, ie …

This paper presents a trajectory planning framework to deal with the highly dynamic
environments for on-road driving. The trajectory optimization problem with parameterized …

Autonomous vehicles must be able to react in a timely manner to typical and unpredictable
situations in urban scenarios. In this connection, motion planning algorithms play a key role …

This paper presents a real-time motion planning scheme for urban autonomous driving that
will be deployed as a basis for cooperative maneuvers defined in the European project …

This paper presents a motion-planning framework for urban autonomous driving at
uncontrolled intersections. The intention and future state of the target vehicles are predicted …

In order to improve the real-time and computational efficiency of autonomous vehicles'
decision-making process, this paper draws on the decision-making behavior of human …

Efficient trajectory planning of autonomous vehicles in complex traffic scenarios is of interest
both academically and in automotive industry. Time efficiency and safety are of key …

The planning of semi-autonomous vehicles in traffic scenarios is a relatively new problem
that contributes towards the goal of making road travel by vehicles free of human drivers. An …