39 citations · 135 across the 22 of their papers we have counts for
6 papers · 1 filter
DriveArena: A Closed-loop Generative Simulation Platform for Autonomous Driving
Xuemeng Yang, Licheng Wen, Yukai Ma +11
This paper presented DriveArena, the first high-fidelity closed-loop simulation system designed for driving agents navigating in real scenarios. DriveArena features a flexible, mod…
Continuously Learning, Adapting, and Improving: A Dual-Process Approach to Autonomous Driving
Jianbiao Mei, Yukai Ma, Xuemeng Yang +11
Autonomous driving has advanced significantly due to sensors, machine learning, and artificial intelligence improvements. However, prevailing methods struggle with intricate scenar…
LimSim++: A Closed-Loop Platform for Deploying Multimodal LLMs in Autonomous Driving
Daocheng Fu, Wenjie Lei, Licheng Wen +5
The emergence of Multimodal Large Language Models ((M)LLMs) has ushered in new avenues in artificial intelligence, particularly for autonomous driving by offering enhanced understa…
Towards Knowledge-driven Autonomous Driving
Xin Li, Yeqi Bai, Pinlong Cai +14
This paper explores the emerging knowledge-driven autonomous driving technologies. Our investigation highlights the limitations of current autonomous driving systems, in particular…
DiLu: A Knowledge-Driven Approach to Autonomous Driving with Large Language Models
Licheng Wen, Daocheng Fu, Xin Li +7
Recent advancements in autonomous driving have relied on data-driven approaches, which are widely adopted but face challenges including dataset bias, overfitting, and uninterpretab…
Drive Like a Human: Rethinking Autonomous Driving with Large Language Models
Daocheng Fu, Xin Li, Licheng Wen +4
In this paper, we explore the potential of using a large language model (LLM) to understand the driving environment in a human-like manner and analyze its ability to reason, interp…