Recent advances in reinforcement learning-based autonomous driving behavior planning: A survey
Autonomous driving (AD) holds the potential to revolutionize transportation efficiency, but its
success hinges on robust behavior planning (BP) mechanisms. Reinforcement learning (RL) …
success hinges on robust behavior planning (BP) mechanisms. Reinforcement learning (RL) …
A survey on autonomous driving datasets: Data statistic, annotation, and outlook
Autonomous driving has rapidly developed and shown promising performance with recent
advances in hardware and deep learning methods. High-quality datasets are fundamental …
advances in hardware and deep learning methods. High-quality datasets are fundamental …
A survey on autonomous driving datasets: Statistics, annotation quality, and a future outlook
Autonomous driving has rapidly developed and shown promising performance due to recent
advances in hardware and deep learning techniques. High-quality datasets are fundamental …
advances in hardware and deep learning techniques. High-quality datasets are fundamental …
Rag-driver: Generalisable driving explanations with retrieval-augmented in-context learning in multi-modal large language model
Robots powered by'blackbox'models need to provide human-understandable explanations
which we can trust. Hence, explainability plays a critical role in trustworthy autonomous …
which we can trust. Hence, explainability plays a critical role in trustworthy autonomous …
Vadv2: End-to-end vectorized autonomous driving via probabilistic planning
Learning a human-like driving policy from large-scale driving demonstrations is promising,
but the uncertainty and non-deterministic nature of planning make it challenging. In this …
but the uncertainty and non-deterministic nature of planning make it challenging. In this …
LimSim++: A Closed-Loop Platform for Deploying Multimodal LLMs in Autonomous Driving
The emergence of Multimodal Large Language Models ((M) LLMs) has ushered in new
avenues in artificial intelligence, particularly for autonomous driving by offering enhanced …
avenues in artificial intelligence, particularly for autonomous driving by offering enhanced …
MAPLM: A Real-World Large-Scale Vision-Language Benchmark for Map and Traffic Scene Understanding
Vision-language generative AI has demonstrated remarkable promise for empowering cross-
modal scene understanding of autonomous driving and high-definition (HD) map systems …
modal scene understanding of autonomous driving and high-definition (HD) map systems …
Drivecot: Integrating chain-of-thought reasoning with end-to-end driving
End-to-end driving has made significant progress in recent years, demonstrating benefits
such as system simplicity and competitive driving performance under both open-loop and …
such as system simplicity and competitive driving performance under both open-loop and …
Skysensegpt: A fine-grained instruction tuning dataset and model for remote sensing vision-language understanding
Remote Sensing Large Multi-Modal Models (RSLMMs) are developing rapidly and
showcase significant capabilities in remote sensing imagery (RSI) comprehension …
showcase significant capabilities in remote sensing imagery (RSI) comprehension …
DrPlanner: Diagnosis and Repair of Motion Planners Using Large Language Models
Motion planners are essential for the safe operation of automated vehicles across various
scenarios. However, no motion planning algorithm has achieved perfection in the literature …
scenarios. However, no motion planning algorithm has achieved perfection in the literature …