Large Language Models in Wargaming: Methodology Application and Robustness
Y Chen, S Chu - Proceedings of the IEEE/CVF Conference …, 2024 - openaccess.thecvf.com
Traditional artificial intelligence (AI) has contributed strategic enhancements to wargaming
but often encounters difficulties in dynamically complex environments and in adapting to …
but often encounters difficulties in dynamically complex environments and in adapting to …
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 …
Summary and Reflections on Pedestrian Trajectory Prediction in the Field of Autonomous Driving
Pedestrian trajectory prediction is a classic and challenging scientific task that involves
complex engineering science and human factors. These challenges have spurred a …
complex engineering science and human factors. These challenges have spurred a …
SMART: Scalable Multi-agent Real-time Simulation via Next-token Prediction
W Wu, X Feng, Z Gao, Y Kan - arXiv preprint arXiv:2405.15677, 2024 - arxiv.org
Data-driven autonomous driving motion generation tasks are frequently impacted by the
limitations of dataset size and the domain gap between datasets, which precludes their …
limitations of dataset size and the domain gap between datasets, which precludes their …
TOD3Cap: Towards 3D Dense Captioning in Outdoor Scenes
3D dense captioning stands as a cornerstone in achieving a comprehensive understanding
of 3D scenes through natural language. It has recently witnessed remarkable achievements …
of 3D scenes through natural language. It has recently witnessed remarkable achievements …
Delving into Multi-modal Multi-task Foundation Models for Road Scene Understanding: From Learning Paradigm Perspectives
Foundation models have indeed made a profound impact on various fields, emerging as
pivotal components that significantly shape the capabilities of intelligent systems. In the …
pivotal components that significantly shape the capabilities of intelligent systems. In the …
DriVLMe: Enhancing LLM-based Autonomous Driving Agents with Embodied and Social Experiences
Recent advancements in foundation models (FMs) have unlocked new prospects in
autonomous driving, yet the experimental settings of these studies are preliminary, over …
autonomous driving, yet the experimental settings of these studies are preliminary, over …
Curse of rarity for autonomous vehicles
The curse of rarity—the rarity of safety-critical events in high-dimensional variable spaces—
presents significant challenges in ensuring the safety of autonomous vehicles using deep …
presents significant challenges in ensuring the safety of autonomous vehicles using deep …
GenFollower: Enhancing Car-Following Prediction with Large Language Models
X Chen, M Peng, PH Tiu, Y Wu, J Chen, M Zhu… - arXiv preprint arXiv …, 2024 - arxiv.org
Accurate modeling of car-following behaviors is essential for various applications in traffic
management and autonomous driving systems. However, current approaches often suffer …
management and autonomous driving systems. However, current approaches often suffer …
Continuously Learning, Adapting, and Improving: A Dual-Process Approach to Autonomous Driving
Autonomous driving has advanced significantly due to sensors, machine learning, and
artificial intelligence improvements. However, prevailing methods struggle with intricate …
artificial intelligence improvements. However, prevailing methods struggle with intricate …