Llm-assist: Enhancing closed-loop planning with language-based reasoning
Although planning is a crucial component of the autonomous driving stack, researchers
have yet to develop robust planning algorithms that are capable of safely handling the …
have yet to develop robust planning algorithms that are capable of safely handling the …
Multi-modal Integrated Prediction and Decision-making with Adaptive Interaction Modality Explorations
Navigating dense and dynamic environments poses a significant challenge for autonomous
driving systems, owing to the intricate nature of multimodal interaction, wherein the actions …
driving systems, owing to the intricate nature of multimodal interaction, wherein the actions …
EasyChauffeur: A Baseline Advancing Simplicity and Efficiency on Waymax
Recent advancements in deep-learning-based driving planners have primarily focused on
elaborate network engineering, yielding limited improvements. This paper diverges from …
elaborate network engineering, yielding limited improvements. This paper diverges from …
Lab2Car: A Versatile Wrapper for Deploying Experimental Planners in Complex Real-world Environments
M Heim, F Suarez-Ruiz, I Bhuiyan, B Brito… - arXiv preprint arXiv …, 2024 - arxiv.org
Human-level autonomous driving is an ever-elusive goal, with planning and decision
making--the cognitive functions that determine driving behavior--posing the greatest …
making--the cognitive functions that determine driving behavior--posing the greatest …
Learning Online Belief Prediction for Efficient POMDP Planning in Autonomous Driving
Effective decision-making in autonomous driving relies on accurate inference of other traffic
agents' future behaviors. To achieve this, we propose an online learning-based behavior …
agents' future behaviors. To achieve this, we propose an online learning-based behavior …
Learning Multiple Probabilistic Decisions from Latent World Model in Autonomous Driving
The autoregressive world model exhibits robust generalization capabilities in vectorized
scene understanding but encounters difficulties in deriving actions due to insufficient …
scene understanding but encounters difficulties in deriving actions due to insufficient …
MIMP: Modular and Interpretable Motion Planning Framework for Safe Autonomous Driving in Complex Real-world Scenarios
CFC Valadares, P Macaluso, G Bartyzel… - 2024 IEEE Intelligent …, 2024 - ieeexplore.ieee.org
Motion planning for autonomous vehicles in complex, real-world urban scenarios is a
fundamental challenge in autonomous driving. To this end, we present MIMP, a Modular and …
fundamental challenge in autonomous driving. To this end, we present MIMP, a Modular and …