most citedAccidentGPT: Accident Analysis and Prevention from V2X Environmental Perception with Multi-modal Large Model

15 citations · 52 across the 11 of their papers we have counts for

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5 papers · 1 filter

cs.RO20241 cited

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…

cs.RO202311 cited

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…

cs.RO20234 cited

EnsembleFollower: A Hybrid Car-Following Framework Based On Reinforcement Learning and Hierarchical Planning

Xu Han, Xianda Chen, Meixin Zhu +3

Car-following models have made significant contributions to our understanding of longitudinal driving behavior. However, they often exhibit limited accuracy and flexibility, as the…

cs.RO202312 cited

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…

cs.RO20233 cited

Bringing Diversity to Autonomous Vehicles: An Interpretable Multi-vehicle Decision-making and Planning Framework

Licheng Wen, Pinlong Cai, Daocheng Fu +2

With the development of autonomous driving, it is becoming increasingly common for autonomous vehicles (AVs) and human-driven vehicles (HVs) to travel on the same roads. Existing s…