Motion planning for autonomous driving: The state of the art and future perspectives
Intelligent vehicles (IVs) have gained worldwide attention due to their increased
convenience, safety advantages, and potential commercial value. Despite predictions of …
convenience, safety advantages, and potential commercial value. Despite predictions of …
[HTML][HTML] Real-time motion planning methods for autonomous on-road driving: State-of-the-art and future research directions
Currently autonomous or self-driving vehicles are at the heart of academia and industry
research because of its multi-faceted advantages that includes improved safety, reduced …
research because of its multi-faceted advantages that includes improved safety, reduced …
[HTML][HTML] Driving environment uncertainty-aware motion planning for autonomous vehicles
Autonomous vehicles require safe motion planning in uncertain environments, which are
largely caused by surrounding vehicles. In this paper, a driving environment uncertainty …
largely caused by surrounding vehicles. In this paper, a driving environment uncertainty …
Differentiable integrated motion prediction and planning with learnable cost function for autonomous driving
Predicting the future states of surrounding traffic participants and planning a safe, smooth,
and socially compliant trajectory accordingly are crucial for autonomous vehicles (AVs) …
and socially compliant trajectory accordingly are crucial for autonomous vehicles (AVs) …
Baidu apollo em motion planner
In this manuscript, we introduce a real-time motion planning system based on the Baidu
Apollo (open source) autonomous driving platform. The developed system aims to address …
Apollo (open source) autonomous driving platform. The developed system aims to address …
Planning and decision-making for autonomous vehicles
W Schwarting, J Alonso-Mora… - Annual Review of Control …, 2018 - annualreviews.org
In this review, we provide an overview of emerging trends and challenges in the field of
intelligent and autonomous, or self-driving, vehicles. Recent advances in the field of …
intelligent and autonomous, or self-driving, vehicles. Recent advances in the field of …
nuplan: A closed-loop ml-based planning benchmark for autonomous vehicles
In this work, we propose the world's first closed-loop ML-based planning benchmark for
autonomous driving. While there is a growing body of ML-based motion planners, the lack of …
autonomous driving. While there is a growing body of ML-based motion planners, the lack of …
Focused trajectory planning for autonomous on-road driving
On-road motion planning for autonomous vehicles is in general a challenging problem. Past
efforts have proposed solutions for urban and highway environments individually. We …
efforts have proposed solutions for urban and highway environments individually. We …
Parting with misconceptions about learning-based vehicle motion planning
The release of nuPlan marks a new era in vehicle motion planning research, offering the first
large-scale real-world dataset and evaluation schemes requiring both precise short-term …
large-scale real-world dataset and evaluation schemes requiring both precise short-term …
Jointly learnable behavior and trajectory planning for self-driving vehicles
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 …
comfortable, and obey the traffic rules. This is usually achieved by two modules: behavior …