Self-driving vehicles will soon be a reality, as main automotive companies have announced
that they will sell their driving automation modes in the 2020s. This technology raises …

This paper presents a hierarchical trajectory planning based on the integration of a sampling
and an optimization method for urban autonomous driving. To manage a complex driving …

This paper focuses on the real-time trajectory planning problem for autonomous vehicles
driving in realistic urban environments. To solve the complex navigation problem, we adopt …

This study proposes a novel integrated local trajectory planning and tracking control
(ILTPTC) framework for autonomous vehicles driving along a reference path with obstacles …

The motion planners used in self-driving vehicles need to generate trajectories that are safe,
comfortable, and obey the traffic rules. This is usually achieved by two modules: behavior …

This paper investigates real-time on-road motion planning algorithms for autonomous
passenger vehicles (APV) in urban environments, and propose a computationally efficient …

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 …

Both path and speed planning play key roles in automated driving, specially when a certain
comfort level is required. This paper proposes a human-like speed planning method for …

Localization plays an important role in autonomous driving since a high level of accuracy in
vehicle localization is indispensable for a safe navigation. Most of the motion planning …

Motion planners for autonomous vehicles must obtain feasible trajectories in real-time
regardless of the complexity of traffic conditions. Planning approaches that discretize the …