12 citations · 22 across the 5 of their papers we have counts for
5 papers
TrafficGPT: Viewing, Processing and Interacting with Traffic Foundation Models
Siyao Zhang, Daocheng Fu, Zhao Zhang +2
With the promotion of chatgpt to the public, Large language models indeed showcase remarkable common sense, reasoning, and planning skills, frequently providing insightful guidance…
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…
LimSim: A Long-term Interactive Multi-scenario Traffic Simulator
Licheng Wen, Daocheng Fu, Song Mao +4
With the growing popularity of digital twin and autonomous driving in transportation, the demand for simulation systems capable of generating high-fidelity and reliable scenarios i…
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…
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…