Path planning for autonomous vehicles in dynamic environments is an important but
challenging problem, due to the constraints of vehicle dynamics and existence of …

In this paper, a trajectory optimization algorithm is proposed, which formulates the lateral
vehicle guidance task along a reference curve as a constrained optimal control problem …

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

In this paper we propose a highly detailed map for the field of autonomous driving. We
introduce the notion of lanelets to represent the drivable environment under both …

In this work we present a simple end-to-end trainable machine learning system capable of
realistically simulating driving experiences. This can be used for verification of self-driving …

In this paper, we propose the Deep Structured self-Driving Network (DSDNet), which
performs object detection, motion prediction, and motion planning with a single neural …

The computational effort of trajectory planning for automated vehicles often increases with
the complexity of the traffic situation. This is particularly problematic in safety-critical …

Motion planning is a core technique for autonomous driving. Nowadays, there still exists a
lot of challenges in motion planning for autonomous driving in complicated environments …

Advanced driver assistance systems or highly automated driving systems for lane change
maneuvers are expected to enhance highway traffic safety, transport efficiency, and driver …

A safe trajectory planning for on-road autonomous driving is a challenging problem owing to
the variety and complexity of driving environments. The problem should involve the …