Surrealdriver: Designing generative driver agent simulation framework in urban contexts based on large language model
Y Jin, X Shen, H Peng, X Liu, J Qin, J Li, J Xie… - arXiv preprint arXiv …, 2023 - arxiv.org
Simulation plays a critical role in the research and development of autonomous driving and
intelligent transportation systems. However, the current simulation platforms exhibit …
intelligent transportation systems. However, the current simulation platforms exhibit …
Dolphins: Multimodal language model for driving
The quest for fully autonomous vehicles (AVs) capable of navigating complex real-world
scenarios with human-like understanding and responsiveness. In this paper, we introduce …
scenarios with human-like understanding and responsiveness. In this paper, we introduce …
A language agent for autonomous driving
Human-level driving is an ultimate goal of autonomous driving. Conventional approaches
formulate autonomous driving as a perception-prediction-planning framework, yet their …
formulate autonomous driving as a perception-prediction-planning framework, yet their …
Towards knowledge-driven autonomous driving
This paper explores the emerging knowledge-driven autonomous driving technologies. Our
investigation highlights the limitations of current autonomous driving systems, in particular …
investigation highlights the limitations of current autonomous driving systems, in particular …
Large language models as traffic signal control agents: Capacity and opportunity
Traffic signal control is crucial for optimizing the efficiency of road network by regulating
traffic light phases. Existing research predominantly focuses on heuristic or reinforcement …
traffic light phases. Existing research predominantly focuses on heuristic or reinforcement …
Vision language models in autonomous driving: A survey and outlook
The applications of Vision-Language Models (VLMs) in the field of Autonomous Driving (AD)
have attracted widespread attention due to their outstanding performance and the ability to …
have attracted widespread attention due to their outstanding performance and the ability to …
Integrating big data analytics in autonomous driving: An unsupervised hierarchical reinforcement learning approach
In the realm of autonomous vehicular systems, there has been a notable increase in end-to-
end algorithms designed for complete self-navigation. Researchers are increasingly …
end algorithms designed for complete self-navigation. Researchers are increasingly …
Human-centric autonomous systems with llms for user command reasoning
The evolution of autonomous driving has made remarkable advancements in recent years,
evolving into a tangible reality. However, a human-centric large-scale adoption hinges on …
evolving into a tangible reality. However, a human-centric large-scale adoption hinges on …
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 …
Feedback-Guided Autonomous Driving
J Zhang, Z Huang, A Ray… - Proceedings of the IEEE …, 2024 - openaccess.thecvf.com
While behavior cloning has recently emerged as a highly successful paradigm for
autonomous driving humans rarely learn to perform complex tasks such as driving via …
autonomous driving humans rarely learn to perform complex tasks such as driving via …